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Sanchez-Cespedes LM, Leasure DR, Tejedor-Garavito N, Amaya Cruz GH, Garcia Velez GA, Mendoza AE, Marín Salazar YA, Esch T, Tatem AJ, Ospina Bohórquez M. Social cartography and satellite-derived building coverage for post-census population estimates in difficult-to-access regions of Colombia. Popul Stud (Camb) 2024; 78:3-20. [PMID: 36977422 DOI: 10.1080/00324728.2023.2190151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 11/22/2022] [Indexed: 03/30/2023]
Abstract
Effective government services rely on accurate population numbers to allocate resources. In Colombia and globally, census enumeration is challenging in remote regions and where armed conflict is occurring. During census preparations, the Colombian National Administrative Department of Statistics conducted social cartography workshops, where community representatives estimated numbers of dwellings and people throughout their regions. We repurposed this information, combining it with remotely sensed buildings data and other geospatial data. To estimate building counts and population sizes, we developed hierarchical Bayesian models, trained using nearby full-coverage census enumerations and assessed using 10-fold cross-validation. We compared models to assess the relative contributions of community knowledge, remotely sensed buildings, and their combination to model fit. The Community model was unbiased but imprecise; the Satellite model was more precise but biased; and the Combination model was best for overall accuracy. Results reaffirmed the power of remotely sensed buildings data for population estimation and highlighted the value of incorporating local knowledge.
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Affiliation(s)
| | - Douglas Ryan Leasure
- Leverhulme Centre for Demographic Science, University of Oxford
- WorldPop, University of Southampton
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2
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Aheto JMK, Olowe ID, Chan HMT, Ekeh A, Dieng B, Fafunmi B, Setayesh H, Atuhaire B, Crawford J, Tatem AJ, Utazi CE. Geospatial Analyses of Recent Household Surveys to Assess Changes in the Distribution of Zero-Dose Children and Their Associated Factors before and during the COVID-19 Pandemic in Nigeria. Vaccines (Basel) 2023; 11:1830. [PMID: 38140234 PMCID: PMC10747017 DOI: 10.3390/vaccines11121830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 11/25/2023] [Accepted: 12/01/2023] [Indexed: 12/24/2023] Open
Abstract
The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and their vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the coronavirus disease 2019 (COVID-19) pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and its associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic, in 2018, and during the pandemic, in 2021, in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of the first dose of diphtheria-tetanus-pertussis-containing vaccine (DTP1), the first dose of measles-containing vaccine (MCV1), and any of the four basic vaccines (bacilli Calmette-Guerin (BCG), oral polio vaccine (OPV0), DTP1, and MCV1), and the corresponding zero-dose estimates independently at a 1 × 1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing the areas in greatest need. At the national level, risk factors related to socioeconomic/demographic status (e.g., maternal education), maternal access to and utilization of health services, and remoteness were strongly associated with the odds of being zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero-dose children in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.
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Affiliation(s)
- Justice Moses K. Aheto
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; (I.D.O.); (H.M.T.C.); (A.J.T.); (C.E.U.)
- Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Accra P.O. Box LG13, Ghana
| | - Iyanuloluwa Deborah Olowe
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; (I.D.O.); (H.M.T.C.); (A.J.T.); (C.E.U.)
| | - Ho Man Theophilus Chan
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; (I.D.O.); (H.M.T.C.); (A.J.T.); (C.E.U.)
- School of Mathematical Sciences, University of Southampton, Southampton SO17 1BJ, UK
| | | | | | | | | | - Brian Atuhaire
- Gavi, The Vaccine Alliance, Geneva, Switzerland; (H.S.); (B.A.); (J.C.)
| | - Jessica Crawford
- Gavi, The Vaccine Alliance, Geneva, Switzerland; (H.S.); (B.A.); (J.C.)
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; (I.D.O.); (H.M.T.C.); (A.J.T.); (C.E.U.)
| | - Chigozie Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; (I.D.O.); (H.M.T.C.); (A.J.T.); (C.E.U.)
- School of Mathematical Sciences, University of Southampton, Southampton SO17 1BJ, UK
- Department of Statistics, Nnamdi Azikiwe University, Awka PMB 5025, Nigeria
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Dwomoh D, Iddi S, Afagbedzi SK, Tejedor-Garavito N, Dotse-Gborgbortsi W, Wright J, Tatem AJ, Nilsen K. Impact of Urban Slum Residence on Coverage of Maternal, Neonatal, and Child Health Service Indicators in the Greater Accra Region of Ghana: an Ecological Time-Series Analysis, 2018-2021. J Urban Health 2023:10.1007/s11524-023-00812-0. [PMID: 37973697 DOI: 10.1007/s11524-023-00812-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/31/2023] [Indexed: 11/19/2023]
Abstract
Among other focus areas, the global Sustainable Development Goals (SDGs) 3 and 11 seek to advance progress toward universal coverage of maternal, neonatal, and child health (MNCH) services and access to safe and affordable housing and basic services by 2030. Governments and development agencies have historically neglected the health and well-being associated with living in urban slums across major capital cities in sub-Saharan Africa since health policies and programs have tended to focus on people living in rural communities. This study assessed the trends and compared inequities in MNCH service utilization between slum and non-slum districts in the Greater Accra region of Ghana. It analyzed information from 29 districts using monthly time-series Health Management Information System (HMIS) data on MNCH service utilization between January 2018 and December 2021. Multivariable quantile regression models with robust standard errors were used to quantify the impact of urban slum residence on MNCH service utilization. We assessed the inequality of MNCH coverage indicators between slum and non-slum districts using the Gini index with bootstrapped standard errors and the generalized Lorenz curve. The results indicate that rates of vaccination coverage and antenatal care (ANC) attendance have declined significantly in slum districts compared to those in non-slum districts. However, skilled birth delivery and postnatal care (PNC) were found to be higher in urban slum areas compared to those in non-urban slum areas. To help achieve the SDGs' targets, it is important for the government of Ghana and other relevant stakeholders to prioritize the implementation of effective policies, programs, and interventions that will improve access to and utilization of ANC and immunization services among urban slum dwellers.
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Affiliation(s)
- Duah Dwomoh
- Department of Biostatistics, School of Public Health, University of Ghana, Accra, Ghana.
| | - Samuel Iddi
- Department of Statistics, School of Physical and Mathematical Sciences, University of Ghana, Accra, Ghana
- Chronic Disease Management Unit, African Population and Health Research Center (APHRC), Nairobi, Kenya
| | - Seth Kwaku Afagbedzi
- Department of Biostatistics, School of Public Health, University of Ghana, Accra, Ghana
| | - Natalia Tejedor-Garavito
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Winfred Dotse-Gborgbortsi
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Jim Wright
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Kristine Nilsen
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
- Department of Social Statistics and Demography, University of Southampton, Southampton, UK
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Wu D, Zhu H, Wan L, Zhang J, Lin W, Sun L, Zhang H, Liu S, Cleary E, Tatem AJ, Xia J, Lai S. Imported and indigenous Plasmodium Vivax and Plasmodium Falciparum malaria in the Hubei Province of China, 2005-2019. Malar J 2023; 22:334. [PMID: 37932775 PMCID: PMC10629024 DOI: 10.1186/s12936-023-04752-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 10/11/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND The Hubei Province in China reported its last indigenous malaria case in September 2012, but imported malaria cases, particularly those related to Plasmodium vivax and Plasmodium falciparum, threaten Hubei's malaria-free status. This study investigated the epidemiological changes in P. vivax and P. falciparum malaria in this province to provide scientific evidence for preventing malaria resurgence. METHODS The prevalence, demographic characteristics, seasonal features, and geographical distribution of malaria were assessed using surveillance data and were compared across three stages: control stage (2005-2009) and elimination stages I (2010-2014) and II (2015-2019). RESULTS In 2005-2019, 8483 malaria cases were reported, including 5599 indigenous P. vivax cases, 275 imported P. vivax cases, 866 imported P. falciparum cases, and 1743 other cases. Imported P. falciparum cases accounted for 0.07% of all cases reported in 2005, but increased to 78.81% in 2019. Most imported P. vivax and P. falciparum malaria occurred among males, aged 21-60 years, during elimination stages I and II. The number of regions affected by imported P. falciparum and P. vivax increased markedly in Hubei from the control stage to elimination stage II. Overall, 1125 imported P. vivax and P. falciparum cases were detected from 47 other nations. Eight imported cases were detected from other provinces in China. From the control stage to elimination stage II, the number of cases of malaria imported from African countries increased, and that of cases imported from Southeast Asian countries decreased. CONCLUSIONS Although Hubei has achieved malaria elimination, it faces challenges in maintaining this status. Hence, imported malaria surveillance need to be strengthened to reduce the risk of malaria re-introduction.
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Affiliation(s)
- Dongni Wu
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Hong Zhu
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Lun Wan
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Juan Zhang
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Wen Lin
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Lingcong Sun
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Huaxun Zhang
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Si Liu
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Eimear Cleary
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Jing Xia
- Institute of Parasitic Disease Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China.
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK.
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Gebrechorkos S, Leyland J, Slater L, Wortmann M, Ashworth PJ, Bennett GL, Boothroyd R, Cloke H, Delorme P, Griffith H, Hardy R, Hawker L, McLelland S, Neal J, Nicholas A, Tatem AJ, Vahidi E, Parsons DR, Darby SE. A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses. Sci Data 2023; 10:611. [PMID: 37696836 PMCID: PMC10495318 DOI: 10.1038/s41597-023-02528-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 08/31/2023] [Indexed: 09/13/2023] Open
Abstract
A large number of historical simulations and future climate projections are available from Global Climate Models, but these are typically of coarse resolution, which limits their effectiveness for assessing local scale changes in climate and attendant impacts. Here, we use a novel statistical downscaling model capable of replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum and minimum temperature, wind speed, air pressure, and relative humidity from 18 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). BCCAQ is calibrated using high-resolution reference datasets and showed a good performance in removing bias from GCMs and reproducing extreme events. The globally downscaled data are available at the Centre for Environmental Data Analysis ( https://doi.org/10.5285/c107618f1db34801bb88a1e927b82317 ) for the historical (1981-2014) and future (2015-2100) periods at 0.25° resolution and at daily time step across three Shared Socioeconomic Pathways (SSP2-4.5, SSP5-3.4-OS and SSP5-8.5). This new climate dataset will be useful for assessing future changes and variability in climate and for driving high-resolution impact assessment models.
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Affiliation(s)
- Solomon Gebrechorkos
- School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK.
- School of Geography and the Environment, University of Oxford, Oxford, UK.
| | - Julian Leyland
- School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Louise Slater
- School of Geography and the Environment, University of Oxford, Oxford, UK
| | - Michel Wortmann
- School of Geography and the Environment, University of Oxford, Oxford, UK
| | - Philip J Ashworth
- School of Applied Sciences, University of Brighton, Sussex, BN2 4AT, Brighton, UK
| | - Georgina L Bennett
- Department of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
| | - Richard Boothroyd
- School of Geographical & Earth Sciences, University of Glasgow, Glasgow, UK
| | - Hannah Cloke
- Geography and Environmental Science, University of Reading, Reading, UK
| | - Pauline Delorme
- Energy and Environment Institute, University of Hull, Hull, UK
| | - Helen Griffith
- Geography and Environmental Science, University of Reading, Reading, UK
| | - Richard Hardy
- Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
| | - Laurence Hawker
- School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
| | | | - Jeffrey Neal
- School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
| | - Andrew Nicholas
- Department of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
| | - Andrew J Tatem
- School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Ellie Vahidi
- Department of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
| | | | - Stephen E Darby
- School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
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6
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Ge Y, Wu X, Zhang W, Wang X, Zhang D, Wang J, Liu H, Ren Z, Ruktanonchai NW, Ruktanonchai CW, Cleary E, Yao Y, Wesolowski A, Cummings DAT, Li Z, Tatem AJ, Lai S. Effects of public-health measures for zeroing out different SARS-CoV-2 variants. Nat Commun 2023; 14:5270. [PMID: 37644012 PMCID: PMC10465600 DOI: 10.1038/s41467-023-40940-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 08/15/2023] [Indexed: 08/31/2023] Open
Abstract
Targeted public health interventions for an emerging epidemic are essential for preventing pandemics. During 2020-2022, China invested significant efforts in strict zero-COVID measures to contain outbreaks of varying scales caused by different SARS-CoV-2 variants. Based on a multi-year empirical dataset containing 131 outbreaks observed in China from April 2020 to May 2022 and simulated scenarios, we ranked the relative intervention effectiveness by their reduction in instantaneous reproduction number. We found that, overall, social distancing measures (38% reduction, 95% prediction interval 31-45%), face masks (30%, 17-42%) and close contact tracing (28%, 24-31%) were most effective. Contact tracing was crucial in containing outbreaks during the initial phases, while social distancing measures became increasingly prominent as the spread persisted. In addition, infections with higher transmissibility and a shorter latent period posed more challenges for these measures. Our findings provide quantitative evidence on the effects of public-health measures for zeroing out emerging contagions in different contexts.
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Affiliation(s)
- Yong Ge
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
- Key Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education, Jiangxi Normal University, Nanchang, China.
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China.
| | - Xilin Wu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Wenbin Zhang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Xiaoli Wang
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - Die Zhang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Poyang Lake Wetland and Watershed Research Ministry of Education, Jiangxi Normal University, Nanchang, China
| | - Jianghao Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Haiyan Liu
- Marine Data Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | | | | | - Eimear Cleary
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Yongcheng Yao
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
- School of Mathematics and Statistics, Zhengzhou Normal University, Zhengzhou, China
| | - Amy Wesolowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Derek A T Cummings
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Zhongjie Li
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
- Institute for Life Sciences, University of Southampton, Southampton, UK.
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.
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7
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McKeen T, Bondarenko M, Kerr D, Esch T, Marconcini M, Palacios-Lopez D, Zeidler J, Valle RC, Juran S, Tatem AJ, Sorichetta A. High-resolution gridded population datasets for Latin America and the Caribbean using official statistics. Sci Data 2023; 10:436. [PMID: 37419895 PMCID: PMC10328919 DOI: 10.1038/s41597-023-02305-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023] Open
Abstract
"Leaving no one behind" is the fundamental objective of the 2030 Agenda for Sustainable Development. Latin America and the Caribbean is marked by social inequalities, whilst its total population is projected to increase to almost 760 million by 2050. In this context, contemporary and spatially detailed datasets that accurately capture the distribution of residential population are critical to appropriately inform and support environmental, health, and developmental applications at subnational levels. Existing datasets are under-utilised by governments due to the non-alignment with their own statistics. Therefore, official statistics at the finest level of administrative units available have been implemented to construct an open-access repository of high-resolution gridded population datasets for 40 countries in Latin American and the Caribbean. These datasets are detailed here, alongside the 'top-down' approach and methods to generate and validate them. Population distribution datasets for each country were created at a resolution of 3 arc-seconds (approximately 100 m at the equator), and are all available from the WorldPop Data Repository.
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Affiliation(s)
- Tom McKeen
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
| | - Maksym Bondarenko
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - David Kerr
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Thomas Esch
- German Aerospace Centre (DLR), Wessling, Germany
| | | | | | | | - R Catalina Valle
- United Nations Population Fund (UNFPA), Regional Office for Latin America and the Caribbean, Panama, Panama
| | - Sabrina Juran
- United Nations Population Fund (UNFPA), Regional Office for Latin America and the Caribbean, Panama, Panama
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Alessandro Sorichetta
- Dipartimento di Scienze della Terra "A. Desio", Università degli Studi di Milano, Milano, Italy
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8
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Qader SH, Utazi CE, Priyatikanto R, Najmaddin P, Hama-Ali EO, Khwarahm NR, Tatem AJ, Dash J. Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems. Sci Total Environ 2023; 869:161716. [PMID: 36690106 DOI: 10.1016/j.scitotenv.2023.161716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/03/2023] [Accepted: 01/15/2023] [Indexed: 06/17/2023]
Abstract
Low levels of agricultural productivity are associated with the persistence of food insecurity, poverty, and other socio-economic stresses. Mapping and monitoring agricultural dynamics and production in real-time at high spatial resolution are essential for ensuring food security and shaping policy interventions. However, an accurate yield estimation might be challenging in some arid and semi-arid regions since input datasets are generally scarce, and access is restricted due to security challenges. This work examines how well Sentinel-2 satellite sensor-derived data, topographic and climatic variables, can be used as covariates to accurately model and predict wheat crop yield at the farm level using statistical models in low data settings of arid and semi-arid regions, using Sulaimani governorate in Iraq as an example. We developed a covariate selection procedure that assessed the correlations between the covariates and their relationships with wheat crop yield. Potential non-linear relationships were investigated in the latter case using regression splines. In the absence of substantial non-linear relationships between the covariates and crop yield, and residual spatial autocorrelation, we fitted a Bayesian multiple linear regression model to model and predict crop yield at 10 m resolution. Out of the covariates tested, our results showed significant relationships between crop yield and mean cumulative NDVI during the growing season, mean elevation, mean end of the season, mean maximum temperature and mean the start of the season at the farm level. For in-sample prediction, we estimated an R2 value of 51 % for the model, whereas for out-of-sample prediction, this was 41 %, both of which indicate reasonable predictive performance. The calculated root-mean-square error for out-of-sample prediction was 69.80, which is less than the standard deviation of 89.23 for crop yield, further showing that the model performed well by reducing prediction variability. Besides crop yield estimates, the model produced uncertainty metrics at 10 m resolution. Overall, this study showed that Sentinel-2 data can be valuable for upscaling field measurement of crop yield in arid and semi-arid regions. In addition, the environmental covariates can strengthen the model predictive power. The method may be applicable in other areas with similar environments, particularly in conflict zones, to increase the availability of agricultural statistics.
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Affiliation(s)
- Sarchil Hama Qader
- School of Geography and Environmental Science, University of Southampton, Southampton, UK; Natural Resources Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq.
| | - Chigozie Edson Utazi
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Rhorom Priyatikanto
- School of Geography and Environmental Science, University of Southampton, Southampton, UK; Research Center for Space, National Research and Innovation Agency, Bandung 40173, Indonesia
| | - Peshawa Najmaddin
- Natural Resources Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq
| | - Emad Omer Hama-Ali
- Biotechnology and Crop Science Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani 46001, Kurdistan Region, Iraq
| | - Nabaz R Khwarahm
- Department of Biology, College of Education, University of Sulaimani, Sulaimani 46001, Kurdistan Region, Iraq
| | - Andrew J Tatem
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Jadu Dash
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
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9
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Pezzulo C, Tejedor-Garavito N, Chan HMT, Dreoni I, Kerr D, Ghosh S, Bonnie A, Bondarenko M, Salasibew M, Tatem AJ. A subnational reproductive, maternal, newborn, child, and adolescent health and development atlas of India. Sci Data 2023; 10:86. [PMID: 36765058 PMCID: PMC9918481 DOI: 10.1038/s41597-023-01961-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/11/2023] [Indexed: 02/12/2023] Open
Abstract
Understanding the fine scale and subnational spatial distribution of reproductive, maternal, newborn, child, and adolescent health and development indicators is crucial for targeting and increasing the efficiency of resources for public health and development planning. National governments are committed to improve the lives of their people, lift the population out of poverty and to achieve the Sustainable Development Goals. We created an open access collection of high resolution gridded and district level health and development datasets of India using mainly the 2015-16 National Family Health Survey (NFHS-4) data, and provide estimates at higher granularity than what is available in NFHS-4, to support policies with spatially detailed data. Bayesian methods for the construction of 5 km × 5 km high resolution maps were applied for a set of indicators where the data allowed (36 datasets), while for some other indicators, only district level data were produced. All data were summarised using the India district administrative boundaries. In total, 138 high resolution and district level datasets for 28 indicators were produced and made openly available.
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Affiliation(s)
- Carla Pezzulo
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK.
| | - Natalia Tejedor-Garavito
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
| | - Ho Man Theophilus Chan
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK.,School of Mathematical Sciences, University of Southampton, Southampton, SO17 1BJ, UK
| | - Ilda Dreoni
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK.,Social Statistics & Demography, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
| | - David Kerr
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
| | - Samik Ghosh
- Children's Investment Fund Foundation (CIFF), London, UK
| | - Amy Bonnie
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
| | - Maksym Bondarenko
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
| | | | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
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10
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Dotse-Gborgbortsi W, Tatem AJ, Matthews Z, Alegana VA, Ofosu A, Wright JA. Quality of maternal healthcare and travel time influence birthing service utilisation in Ghanaian health facilities: a geographical analysis of routine health data. BMJ Open 2023; 13:e066792. [PMID: 36657766 PMCID: PMC9853258 DOI: 10.1136/bmjopen-2022-066792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVES To investigate how the quality of maternal health services and travel times to health facilities affect birthing service utilisation in Eastern Region, Ghana. DESIGN The study is a cross-sectional spatial interaction analysis of birth service utilisation patterns. Routine birth data were spatially linked to quality care, service demand and travel time data. SETTING 131 Health facilities (public, private and faith-based) in 33 districts in Eastern Region, Ghana. PARTICIPANTS Women who gave birth in health facilities in the Eastern Region, Ghana in 2017. OUTCOME MEASURES The count of women giving birth, the quality of birthing care services and the geographic coverage of birthing care services. RESULTS As travel time from women's place of residence to the health facility increased up to two2 hours, the utilisation rate markedly decreased. Higher quality of maternal health services haves a larger, positive effect on utilisation rates than service proximity. The quality of maternal health services was higher in hospitals than in primary care facilities. Most women (88.6%) travelling via mechanised transport were within two2 hours of any birthing service. The majority (56.2%) of women were beyond the two2 -hour threshold of critical comprehensive emergency obstetric and newborn care (CEmONC) services. Few CEmONC services were in urban centres, disadvantaging rural populations. CONCLUSIONS To increase birthing service utilisation in Ghana, higher quality health facilities should be located closer to women, particularly in rural areas. Beyond Ghana, routinely collected birth records could be used to understand the interaction of service proximity and quality.
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Affiliation(s)
| | - Andrew J Tatem
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Zoe Matthews
- Department of Social Statistics and Demography, University of Southampton, Southampton, UK
| | - Victor A Alegana
- Population Health Unit-Wellcome Trust Research Programme, Kenya Medical Research Institute, Nairobi, Kenya
| | - Anthony Ofosu
- Headquarters, Ghana Health Service, Accra, Greater Accra, Ghana
| | - Jim A Wright
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
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11
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Utazi CE, Aheto JMK, Wigley A, Tejedor-Garavito N, Bonnie A, Nnanatu CC, Wagai J, Williams C, Setayesh H, Tatem AJ, Cutts FT. Mapping the distribution of zero-dose children to assess the performance of vaccine delivery strategies and their relationships with measles incidence in Nigeria. Vaccine 2023; 41:170-181. [PMID: 36414476 DOI: 10.1016/j.vaccine.2022.11.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 10/19/2022] [Accepted: 11/14/2022] [Indexed: 11/21/2022]
Abstract
Geographically precise identification and targeting of populations at risk of vaccine-preventable diseases has gained renewed attention within the global health community over the last few years. District level estimates of vaccination coverage and corresponding zero-dose prevalence constitute a potentially useful evidence base to evaluate the performance of vaccination strategies. These estimates are also valuable for identifying missed communities, hence enabling targeted interventions and better resource allocation. Here, we fit Bayesian geostatistical models to map the routine coverage of the first doses of diphtheria-tetanus-pertussis vaccine (DTP1) and measles-containing vaccine (MCV1) and corresponding zero-dose estimates in Nigeria at 1x1 km resolution and the district level using geospatial data sets. We also map MCV1 coverage before and after the 2019 measles vaccination campaign in the northern states to further explore variations in routine vaccine coverage and to evaluate the effectiveness of both routine immunization (RI) and campaigns in reaching zero-dose children. Additionally, we map the spatial distributions of reported measles cases during 2018 to 2020 and explore their relationships with MCV zero-dose prevalence to highlight the public health implications of varying performance of vaccination strategies across the country. Our analysis revealed strong similarities between the spatial distributions of DTP and MCV zero dose prevalence, with districts with the highest prevalence concentrated mostly in the northwest and the northeast, but also in other areas such as Lagos state and the Federal Capital Territory. Although the 2019 campaign reduced MCV zero-dose prevalence substantially in the north, pockets of vulnerabilities remained in areas that had among the highest prevalence prior to the campaign. Importantly, we found strong correlations between measles case counts and MCV RI zero-dose estimates, which provides a strong indication that measles incidence in the country is mostly affected by RI coverage. Our analyses reveal an urgent and highly significant need to strengthen the country's RI program as a longer-term measure for disease control, whilst ensuring effective campaigns in the short term.
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Affiliation(s)
- C Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; Southampton Statistical Sciences Research Institute, University of Southampton, Southampton SO17 1BJ, UK; Department of Statistics, Nnamdi Azikiwe University, Awka PMB 5025, Nigeria.
| | - Justice M K Aheto
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Accra, Ghana
| | - Adelle Wigley
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Natalia Tejedor-Garavito
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Amy Bonnie
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Christopher C Nnanatu
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK; Department of Statistics, Nnamdi Azikiwe University, Awka PMB 5025, Nigeria
| | - John Wagai
- World Health Organization Consultant, Abuja, Nigeria
| | - Cheryl Williams
- U.S. Centers for Disease Control and Prevention, Nigeria Country Office, Abuja, Nigeria
| | | | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Felicity T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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12
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Utazi CE, Aheto JMK, Chan HMT, Tatem AJ, Sahu SK. Conditional probability and ratio-based approaches for mapping the coverage of multi-dose vaccines. Stat Med 2022; 41:5662-5678. [PMID: 36129171 PMCID: PMC9826002 DOI: 10.1002/sim.9586] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 06/10/2022] [Accepted: 09/09/2022] [Indexed: 01/11/2023]
Abstract
Many vaccines are often administered in multiple doses to boost their effectiveness. In the case of childhood vaccines, the coverage maps of the doses and the differences between these often constitute an evidence base to guide investments in improving access to vaccination services and health system performance in low and middle-income countries. A major problem often encountered when mapping the coverage of multi-dose vaccines is the need to ensure that the coverage maps decrease monotonically with successive doses. That is, for doses i $$ i $$ and j $$ j $$ , i < j ⇒ p i ( s ) ≥ p j ( s ) $$ i<j\Rightarrow {p}_i\left(\boldsymbol{s}\right)\ge {p}_j\left(\boldsymbol{s}\right) $$ , where p i ( s ) $$ {p}_i\left(\boldsymbol{s}\right) $$ is the coverage of dose i $$ i $$ at spatial location s $$ \boldsymbol{s} $$ . Here, we explore conditional probability (CP) and ratio-based (RB) approaches for mapping p i ( s ) $$ {p}_i\left(\boldsymbol{s}\right) $$ , embedded within a binomial geostatistical modeling framework, to address this problem. The fully Bayesian model is implemented using the INLA and SPDE approaches. Using a simulation study, we find that both approaches perform comparably for out-of-sample estimation under varying point-level sample size distributions. We apply the methodology to map the coverage of the three doses of diphtheria-tetanus-pertussis vaccine using data from the 2018 Nigeria Demographic and Health Survey. The coverage maps produced using both approaches are almost indistinguishable, although the CP approach yielded more precise estimates on average in this application. We also provide estimates of zero-dose children and the dropout rates between the doses. The methodology is straightforward to implement and can be applied to other vaccines and geographical contexts.
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Affiliation(s)
- Chigozie Edson Utazi
- WorldPop, School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonUK,School of Mathematical SciencesUniversity of SouthamptonSouthamptonUK
| | - Justice Moses K. Aheto
- WorldPop, School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonUK
| | - Ho Man Theophilus Chan
- WorldPop, School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonUK,School of Mathematical SciencesUniversity of SouthamptonSouthamptonUK
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonUK
| | - Sujit K. Sahu
- School of Mathematical SciencesUniversity of SouthamptonSouthamptonUK
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13
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Darin E, Kuepie M, Bassinga H, Boo G, Tatem AJ. La population vue du ciel : quand l’imagerie satellite vient au secours du recensement. Population 2022. [DOI: 10.3917/popu.2203.0467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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14
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Tatem AJ. Small area population denominators for improved disease surveillance and response. Epidemics 2022; 41:100641. [PMID: 36228440 PMCID: PMC9534780 DOI: 10.1016/j.epidem.2022.100641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 05/12/2022] [Accepted: 10/04/2022] [Indexed: 12/29/2022] Open
Abstract
The Covid-19 pandemic has highlighted the value of strong surveillance systems in supporting our abilities to respond rapidly and effectively in mitigating the impacts of infectious diseases. A cornerstone of such systems is basic subnational scale data on populations and their demographics, which enable the scale of outbreaks to be assessed, risk to specific groups to be determined and appropriate interventions to be designed. Ongoing weaknesses and gaps in such data have however been highlighted by the pandemic. These can include outdated or inaccurate census data and a lack of administrative and registry systems to update numbers, particularly in low and middle income settings. Efforts to design and implement globally consistent geospatial modelling methods for the production of small area demographic data that can be flexibly integrated into health-focussed surveillance and information systems have been made, but these often remain based on outdated population data or uncertain projections. In recent years, efforts have been made to capitalise on advances in computing power, satellite imagery and new forms of digital data to construct methods for estimating small area population distributions across national and regional scales in the absence of full enumeration. These are starting to be used to complement more traditional data collection approaches, especially in the delivery of health interventions, but barriers remain to their widespread adoption and use in disease surveillance and response. Here an overview of these approaches is presented, together with discussion of future directions and needs.
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Affiliation(s)
- A J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
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15
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Chamberlain HR, Lazar AN, Tatem AJ. High-resolution estimates of social distancing feasibility, mapped for urban areas in sub-Saharan Africa. Sci Data 2022; 9:711. [PMCID: PMC9673897 DOI: 10.1038/s41597-022-01799-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 10/21/2022] [Indexed: 11/19/2022] Open
Abstract
AbstractSocial distancing has been widely-implemented as a public health measure during the COVID-19 pandemic. Despite widespread application of social distancing guidance, the feasibility of people adhering to such guidance varies in different settings, influenced by population density, the built environment and a range of socio-economic factors. Social distancing constraints however have only been identified and mapped for limited areas. Here, we present an ease of social distancing index, integrating metrics on urban form and population density derived from new multi-country building footprint datasets and gridded population estimates. The index dataset provides estimates of social distancing feasibility, mapped at high-resolution for urban areas across 50 countries in sub-Saharan Africa.
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16
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Ferreira LZ, Utazi CE, Huicho L, Nilsen K, Hartwig FP, Tatem AJ, Barros AJD. Geographic inequalities in health intervention coverage – mapping the composite coverage index in Peru using geospatial modelling. BMC Public Health 2022; 22:2104. [PMID: 36397019 PMCID: PMC9670533 DOI: 10.1186/s12889-022-14371-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 10/14/2022] [Indexed: 11/18/2022] Open
Abstract
Background The composite coverage index (CCI) provides an integrated perspective towards universal health coverage in the context of reproductive, maternal, newborn and child health. Given the sample design of most household surveys does not provide coverage estimates below the first administrative level, approaches for achieving more granular estimates are needed. We used a model-based geostatistical approach to estimate the CCI at multiple resolutions in Peru. Methods We generated estimates for the eight indicators on which the CCI is based for the departments, provinces, and areas of 5 × 5 km of Peru using data from two national household surveys carried out in 2018 and 2019 plus geospatial covariates. Bayesian geostatistical models were fit using the INLA-SPDE approach. We assessed model fit using cross-validation at the survey cluster level and by comparing modelled and direct survey estimates at the department-level. Results CCI coverage in the provinces along the coast was consistently higher than in the remainder of the country. Jungle areas in the north and east presented the lowest coverage levels and the largest gaps between and within provinces. The greatest inequalities were found, unsurprisingly, in the largest provinces where populations are scattered in jungle territory and are difficult to reach. Conclusions Our study highlighted provinces with high levels of inequality in CCI coverage indicating areas, mostly low-populated jungle areas, where more attention is needed. We also uncovered other areas, such as the border with Bolivia, where coverage is lower than the coastal provinces and should receive increased efforts. More generally, our results make the case for high-resolution estimates to unveil geographic inequities otherwise hidden by the usual levels of survey representativeness. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-14371-7.
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17
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Wigley A, Lorin J, Hogan D, Utazi CE, Hagedorn B, Dansereau E, Tatem AJ, Tejedor-Garavito N. Estimates of the number and distribution of zero-dose and under-immunised children across remote-rural, urban, and conflict-affected settings in low and middle-income countries. PLOS Glob Public Health 2022; 2:e0001126. [PMID: 36962682 PMCID: PMC10021885 DOI: 10.1371/journal.pgph.0001126] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 10/05/2022] [Indexed: 02/11/2023]
Abstract
While there has been great success in increasing the coverage of new childhood vaccines globally, expanding routine immunization to reliably reach all children and communities has proven more challenging in many low- and middle-income countries. Achieving this requires vaccination strategies and interventions that identify and target those unvaccinated, guided by the most current and detailed data regarding their size and spatial distribution. Through the integration and harmonisation of a range of geospatial data sets, including population, vaccination coverage, travel-time, settlement type, and conflict locations. We estimated the numbers of children un- or under-vaccinated for measles and diphtheria-tetanus-pertussis, within remote-rural, urban, and conflict-affected locations. We explored how these numbers vary both nationally and sub-nationally, and assessed what proportions of children these categories captured, for 99 lower- and middle-income countries, for which data was available. We found that substantial heterogeneities exist both between and within countries. Of the total 14,030,486 children unvaccinated for DTP1, over 11% (1,656,757) of un- or under-vaccinated children were in remote-rural areas, more than 28% (2,849,671 and 1,129,915) in urban and peri-urban areas, and up to 60% in other settings, with nearly 40% found to be within 1-hour of the nearest town or city (though outside of urban/peri-urban areas). Of the total number of those unvaccinated, we estimated between 6% and 15% (826,976 to 2,068,785) to be in conflict-affected locations, based on either broad or narrow definitions of conflict. Our estimates provide insights into the inequalities in vaccination coverage, with the distributions of those unvaccinated varying significantly by country, region, and district. We demonstrate the need for further inquiry and characterisation of those unvaccinated, the thresholds used to define these, and for more country-specific and targeted approaches to defining such populations in the strategies and interventions used to reach them.
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Affiliation(s)
- Adelle Wigley
- WorldPop, Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, United Kingdom
| | - Josh Lorin
- Gavi, The Vaccine Alliance, Geneva, Switzerland
| | - Dan Hogan
- Gavi, The Vaccine Alliance, Geneva, Switzerland
| | - C. Edson Utazi
- WorldPop, Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, United Kingdom
| | - Brittany Hagedorn
- Institute for Disease Modelling, Bill & Melinda Gates Foundation, Seattle, Washington, WA, United States of America
| | - Emily Dansereau
- Institute for Disease Modelling, Bill & Melinda Gates Foundation, Seattle, Washington, WA, United States of America
| | - Andrew J. Tatem
- WorldPop, Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, United Kingdom
| | - Natalia Tejedor-Garavito
- WorldPop, Geography and Environmental Science, University of Southampton, Highfield Campus, Southampton, United Kingdom
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18
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Hierink F, Boo G, Macharia PM, Ouma PO, Timoner P, Levy M, Tschirhart K, Leyk S, Oliphant N, Tatem AJ, Ray N. Differences between gridded population data impact measures of geographic access to healthcare in sub-Saharan Africa. Commun Med (Lond) 2022; 2:117. [PMID: 36124060 PMCID: PMC9481590 DOI: 10.1038/s43856-022-00179-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 09/01/2022] [Indexed: 12/04/2022] Open
Abstract
Background Access to healthcare is imperative to health equity and well-being. Geographic access to healthcare can be modeled using spatial datasets on local context, together with the distribution of existing health facilities and populations. Several population datasets are currently available, but their impact on accessibility analyses is unknown. In this study, we model the geographic accessibility of public health facilities at 100-meter resolution in sub-Saharan Africa and evaluate six of the most popular gridded population datasets for their impact on coverage statistics at different administrative levels. Methods Travel time to nearest health facilities was calculated by overlaying health facility coordinates on top of a friction raster accounting for roads, landcover, and physical barriers. We then intersected six different gridded population datasets with our travel time estimates to determine accessibility coverages within various travel time thresholds (i.e., 30, 60, 90, 120, 150, and 180-min). Results Here we show that differences in accessibility coverage can exceed 70% at the sub-national level, based on a one-hour travel time threshold. The differences are most notable in large and sparsely populated administrative units and dramatically shape patterns of healthcare accessibility at national and sub-national levels. Conclusions The results of this study show how valuable and critical a comparative analysis between population datasets is for the derivation of coverage statistics that inform local policies and monitor global targets. Large differences exist between the datasets and the results underscore an essential source of uncertainty in accessibility analyses that should be systematically assessed.
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Affiliation(s)
- Fleur Hierink
- GeoHealth group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland
| | - Gianluca Boo
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
- Small Arms Survey, The Graduate Institute, Geneva, Switzerland
| | - Peter M. Macharia
- Population Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Health Informatics, Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK
| | - Paul O. Ouma
- Population Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, Nairobi, Kenya
| | - Pablo Timoner
- GeoHealth group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland
| | - Marc Levy
- CIESIN, The Center for International Earth Science Information Network, Columbia University, Palisades, NY USA
| | - Kevin Tschirhart
- CIESIN, The Center for International Earth Science Information Network, Columbia University, Palisades, NY USA
| | - Stefan Leyk
- Department of Geography, University of Colorado in Boulder, Boulder, CO USA
| | - Nicholas Oliphant
- The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Nicolas Ray
- GeoHealth group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland
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19
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Chamberlain HR, Macharia PM, Tatem AJ. Mapping urban physical distancing constraints, sub-Saharan Africa: a case study from Kenya. Bull World Health Organ 2022; 100:562-569. [PMID: 36062248 PMCID: PMC9421546 DOI: 10.2471/blt.21.287572] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 05/31/2022] [Accepted: 06/01/2022] [Indexed: 11/27/2022] Open
Abstract
With the onset of the coronavirus disease 2019 (COVID-19) pandemic, public health measures such as physical distancing were recommended to reduce transmission of the virus causing the disease. However, the same approach in all areas, regardless of context, may lead to measures being of limited effectiveness and having unforeseen negative consequences, such as loss of livelihoods and food insecurity. A prerequisite to planning and implementing effective, context-appropriate measures to slow community transmission is an understanding of any constraints, such as the locations where physical distancing would not be possible. Focusing on sub-Saharan Africa, we outline and discuss challenges that are faced by residents of urban informal settlements in the ongoing COVID-19 pandemic. We describe how new geospatial data sets can be integrated to provide more detailed information about local constraints on physical distancing and can inform planning of alternative ways to reduce transmission of COVID-19 between people. We include a case study for Nairobi County, Kenya, with mapped outputs which illustrate the intra-urban variation in the feasibility of physical distancing and the expected difficulty for residents of many informal settlement areas. Our examples demonstrate the potential of new geospatial data sets to provide insights and support to policy-making for public health measures, including COVID-19.
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Affiliation(s)
- Heather R Chamberlain
- WorldPop, Geography and Environmental Science, Building 39, University of Southampton, University Road, Southampton, SO17 1BJ, England
| | - Peter M Macharia
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Andrew J Tatem
- WorldPop, Geography and Environmental Science, Building 39, University of Southampton, University Road, Southampton, SO17 1BJ, England
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Dotse-Gborgbortsi W, Nilsen K, Ofosu A, Matthews Z, Tejedor-Garavito N, Wright J, Tatem AJ. Distance is “a big problem”: a geographic analysis of reported and modelled proximity to maternal health services in Ghana. BMC Pregnancy Childbirth 2022; 22:672. [PMID: 36045351 PMCID: PMC9429654 DOI: 10.1186/s12884-022-04998-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 08/22/2022] [Indexed: 11/10/2022] Open
Abstract
Background Geographic barriers to healthcare are associated with adverse maternal health outcomes. Modelling travel times using georeferenced data is becoming common in quantifying physical access. Multiple Demographic and Health Surveys ask women about distance-related problems accessing healthcare, but responses have not been evaluated against modelled travel times. This cross-sectional study aims to compare reported and modelled distance by socio-demographic characteristics and evaluate their relationship with skilled birth attendance. Also, we assess the socio-demographic factors associated with self-reported distance problems in accessing healthcare. Methods Distance problems and socio-demographic characteristics reported by 2210 women via the 2017 Ghana Maternal Health Survey were included in analysis. Geospatial methods were used to model travel time to the nearest health facility using roads, rivers, land cover, travel speeds, cluster locations and health facility locations. Logistic regressions were used to predict skilled birth attendance and self-reported distance problems. Results Women reporting distance challenges accessing healthcare had significantly longer travel times to the nearest health facility. Poverty significantly increased the odds of reporting challenges with distance. In contrast, living in urban areas and being registered with health insurance reduced the odds of reporting distance challenges. Women with a skilled attendant at birth, four or more skilled antenatal appointments and timely skilled postnatal care had shorter travel times to the nearest health facility. Generally, less educated, poor, rural women registered with health insurance had longer travel times to their nearest health facility. After adjusting for socio-demographic characteristics, the following factors increased the odds of skilled birth attendance: wealth, health insurance, higher education, living in urban areas, and completing four or more antenatal care appointments. Conclusion Studies relying on modelled travel times to nearest facility should recognise the differential impact of geographic access to healthcare on poor rural women. Physical access to maternal health care should be scaled up in rural areas and utilisation increased by improving livelihoods. Supplementary Information The online version contains supplementary material available at 10.1186/s12884-022-04998-0.
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Lai S, Bogoch II, Ruktanonchai NW, Watts A, Lu X, Yang W, Yu H, Khan K, Tatem AJ. Assessing spread risk of COVID-19 within and beyond China in early 2020. Data Science and Management 2022. [PMCID: PMC9411104 DOI: 10.1016/j.dsm.2022.08.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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22
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Tatem AJ. Small area population denominators for improved disease surveillance and response. Epidemics 2022; 40:100597. [PMID: 35749928 PMCID: PMC9212890 DOI: 10.1016/j.epidem.2022.100597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 06/13/2022] [Indexed: 11/30/2022] Open
Abstract
The Covid-19 pandemic has highlighted the value of strong surveillance systems in supporting our abilities to respond rapidly and effectively in mitigating the impacts of infectious diseases. A cornerstone of such systems is basic subnational scale data on populations and their demographics, which enable the scale of outbreaks to be assessed, risk to specific groups to be determined and appropriate interventions to be designed. Ongoing weaknesses and gaps in such data have however been highlighted by the pandemic. These can include outdated or inaccurate census data and a lack of administrative and registry systems to update numbers, particularly in low and middle income settings. Efforts to design and implement globally consistent geospatial modelling methods for the production of small area demographic data that can be flexibly integrated into health-focussed surveillance and information systems have been made, but these often remain based on outdated population data or uncertain projections. In recent years, efforts have been made to capitalise on advances in computing power, satellite imagery and new forms of digital data to construct methods for estimating small area population distributions across national and regional scales in the absence of full enumeration. These are starting to be used to complement more traditional data collection approaches, especially in the delivery of health interventions, but barriers remain to their widespread adoption and use in disease surveillance and response. Here an overview of these approaches is presented, together with discussion of future directions and needs.
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Affiliation(s)
- A J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
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23
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Dotse-Gborgbortsi W, Tatem AJ, Matthews Z, Alegana V, Ofosu A, Wright J. Delineating natural catchment health districts with routinely collected health data from women's travel to give birth in Ghana. BMC Health Serv Res 2022; 22:772. [PMID: 35698112 PMCID: PMC9190150 DOI: 10.1186/s12913-022-08125-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 05/26/2022] [Indexed: 11/10/2022] Open
Abstract
Background Health service areas are essential for planning, policy and managing public health interventions. In this study, we delineate health service areas from routinely collected health data as a robust geographic basis for presenting access to maternal care indicators. Methods A zone design algorithm was adapted to delineate health service areas through a cross-sectional, ecological study design. Health sub-districts were merged into health service areas such that patient flows across boundaries were minimised. Delineated zones and existing administrative boundaries were used to provide estimates of access to maternal health services. We analysed secondary data comprising routinely collected health records from 32,921 women attending 27 hospitals to give birth, spatial demographic data, a service provision assessment on the quality of maternal healthcare and health sub-district boundaries from Eastern Region, Ghana. Results Clear patterns of cross border movement to give birth emerged from the analysis, but more women originated closer to the hospitals. After merging the 250 sub-districts in 33 districts, 11 health service areas were created. The minimum percent of internal flows of women giving birth within any health service area was 97.4%. Because the newly delineated boundaries are more “natural” and sensitive to observed flow patterns, when we calculated areal indicator estimates, they showed a marked improvement over the existing administrative boundaries, with the inclusion of a hospital in every health service area. Conclusion Health planning can be improved by using routine health data to delineate natural catchment health districts. In addition, data-driven geographic boundaries derived from public health events will improve areal health indicator estimates, planning and interventions.
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Affiliation(s)
- Winfred Dotse-Gborgbortsi
- School of Geography and Environmental Science, University of Southampton, Southampton, S017 1BJ, UK. .,WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
| | - Andrew J Tatem
- School of Geography and Environmental Science, University of Southampton, Southampton, S017 1BJ, UK.,WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Zoë Matthews
- Department of Social Statistics and Demography, University of Southampton, Southampton, UK
| | - Victor Alegana
- Population Health Unit, Kenya Medical Research Institute - Wellcome Trust Research Programme, Nairobi, Kenya
| | | | - Jim Wright
- School of Geography and Environmental Science, University of Southampton, Southampton, S017 1BJ, UK
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24
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Ge Y, Zhang WB, Wu X, Ruktanonchai CW, Liu H, Wang J, Song Y, Liu M, Yan W, Yang J, Cleary E, Qader SH, Atuhaire F, Ruktanonchai NW, Tatem AJ, Lai S. Untangling the changing impact of non-pharmaceutical interventions and vaccination on European COVID-19 trajectories. Nat Commun 2022; 13:3106. [PMID: 35661759 PMCID: PMC9166696 DOI: 10.1038/s41467-022-30897-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 05/24/2022] [Indexed: 12/27/2022] Open
Abstract
Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect of NPIs and vaccination on reducing COVID-19 transmission, based on a large-scale dataset including epidemiological parameters, virus variants, vaccines, and climate factors in Europe from August 2020 to October 2021. We found that (1) the combined effect of NPIs and vaccination resulted in a 53% (95% confidence interval: 42–62%) reduction in reproduction number by October 2021, whereas NPIs and vaccination reduced the transmission by 35% and 38%, respectively; (2) compared with vaccination, the change of NPI effect was less sensitive to emerging variants; (3) the relative effect of NPIs declined 12% from May 2021 due to a lower stringency and the introduction of vaccination strategies. Our results demonstrate that NPIs were complementary to vaccination in an effort to reduce COVID-19 transmission, and the relaxation of NPIs might depend on vaccination rates, control targets, and vaccine effectiveness concerning extant and emerging variants. Non-pharmaceutical interventions (NPIs) and COVID-19 vaccination have been implemented concurrently, making their relative effects difficult to measure. Here, the authors show that effects of NPIs reduced as vaccine coverage increased, but that NPIs could still be important in the context of more transmissible variants.
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Affiliation(s)
- Yong Ge
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. .,College of Resources and Environment, University of Academy of Sciences, Beijing, China.
| | - Wen-Bin Zhang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Academy of Sciences, Beijing, China.,Lancaster Environment Center, Faculty of Science and Technology, Lancaster University, Lancaster, UK
| | - Xilin Wu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | | | - Haiyan Liu
- Marine Data Center, South Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Jianghao Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Yongze Song
- School of Design and the Built Environment, Curtin University, Perth, Australia
| | - Mengxiao Liu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.,College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Wei Yan
- Respiratory Medicine Department, Peking University Third Hospital, Beijing, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.,Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
| | - Eimear Cleary
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Sarchil H Qader
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,Natural Resources Department, College of Agricultural Engineering Sciences, University of Sulaimani; Sulaimani 334, Kurdistan Region, Sulaymaniyah, Iraq
| | - Fatumah Atuhaire
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,School of Mathematical Sciences, University of Southampton, Southampton, UK
| | | | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
| | - Shengjie Lai
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China. .,WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK. .,Institute for Life Sciences, University of Southampton, Southampton, UK.
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25
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Aheto JMK, Pannell O, Dotse-Gborgbortsi W, Trimner MK, Tatem AJ, Rhoda DA, Cutts FT, Utazi CE. Multilevel analysis of predictors of multiple indicators of childhood vaccination in Nigeria. PLoS One 2022; 17:e0269066. [PMID: 35613138 PMCID: PMC9132327 DOI: 10.1371/journal.pone.0269066] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 05/13/2022] [Indexed: 11/18/2022] Open
Abstract
Background Substantial inequalities exist in childhood vaccination coverage levels. To increase vaccine uptake, factors that predict vaccination coverage in children should be identified and addressed. Methods Using data from the 2018 Nigeria Demographic and Health Survey and geospatial data sets, we fitted Bayesian multilevel binomial and multinomial logistic regression models to analyse independent predictors of three vaccination outcomes: receipt of the first dose of Pentavalent vaccine (containing diphtheria-tetanus-pertussis, Hemophilus influenzae type B and Hepatitis B vaccines) (PENTA1) (n = 6059) and receipt of the third dose having received the first (PENTA3/1) (n = 3937) in children aged 12–23 months, and receipt of measles vaccine (MV) (n = 11839) among children aged 12–35 months. Results Factors associated with vaccination were broadly similar for documented versus recall evidence of vaccination. Based on any evidence of vaccination, we found that health card/document ownership, receipt of vitamin A and maternal educational level were significantly associated with each outcome. Although the coverage of each vaccine dose was higher in urban than rural areas, urban residence was not significant in multivariable analyses that included travel time. Indicators relating to socio-economic status, as well as ethnic group, skilled birth attendance, lower travel time to the nearest health facility and problems seeking health care were significantly associated with both PENTA1 and MV. Maternal religion was related to PENTA1 and PENTA3/1 and maternal age related to MV and PENTA3/1; other significant variables were associated with one outcome each. Substantial residual community level variances in different strata were observed in the fitted models for each outcome. Conclusion Our analysis has highlighted socio-demographic and health care access factors that affect not only beginning but completing the vaccination series in Nigeria. Other factors not measured by the DHS such as health service quality and community attitudes should also be investigated and addressed to tackle inequities in coverage.
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Affiliation(s)
- Justice Moses K. Aheto
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
- Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Accra, Ghana
- * E-mail: ,
| | - Oliver Pannell
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Winfred Dotse-Gborgbortsi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Mary K. Trimner
- Biostat Global Consulting, Worthington, OH, United States of America
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Dale A. Rhoda
- Biostat Global Consulting, Worthington, OH, United States of America
| | - Felicity T. Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - C. Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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26
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Muchiri SK, Muthee R, Kiarie H, Sitienei J, Agweyu A, Atkinson PM, Edson Utazi C, Tatem AJ, Alegana VA. Unmet need for COVID-19 vaccination coverage in Kenya. Vaccine 2022; 40:2011-2019. [PMID: 35184925 PMCID: PMC8841160 DOI: 10.1016/j.vaccine.2022.02.035] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 01/30/2022] [Accepted: 02/07/2022] [Indexed: 11/30/2022]
Abstract
COVID-19 has impacted the health and livelihoods of billions of people since it emerged in 2019. Vaccination for COVID-19 is a critical intervention that is being rolled out globally to end the pandemic. Understanding the spatial inequalities in vaccination coverage and access to vaccination centres is important for planning this intervention nationally. Here, COVID-19 vaccination data, representing the number of people given at least one dose of vaccine, a list of the approved vaccination sites, population data and ancillary GIS data were used to assess vaccination coverage, using Kenya as an example. Firstly, physical access was modelled using travel time to estimate the proportion of population within 1 hour of a vaccination site. Secondly, a Bayesian conditional autoregressive (CAR) model was used to estimate the COVID-19 vaccination coverage and the same framework used to forecast coverage rates for the first quarter of 2022. Nationally, the average travel time to a designated COVID-19 vaccination site (n = 622) was 75.5 min (Range: 62.9 - 94.5 min) and over 87% of the population >18 years reside within 1 hour to a vaccination site. The COVID-19 vaccination coverage in December 2021 was 16.70% (95% CI: 16.66 - 16.74) - 4.4 million people and was forecasted to be 30.75% (95% CI: 25.04 - 36.96) - 8.1 million people by the end of March 2022. Approximately 21 million adults were still unvaccinated in December 2021 and, in the absence of accelerated vaccine uptake, over 17.2 million adults may not be vaccinated by end March 2022 nationally. Our results highlight geographic inequalities at sub-national level and are important in targeting and improving vaccination coverage in hard-to-reach populations. Similar mapping efforts could help other countries identify and increase vaccination coverage for such populations.
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Affiliation(s)
- Samuel K Muchiri
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
| | - Rose Muthee
- Department of Health Informatics, Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Hellen Kiarie
- Department of Health Informatics, Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Joseph Sitienei
- Department of Health Informatics, Monitoring and Evaluation, Ministry of Health, Nairobi, Kenya
| | - Ambrose Agweyu
- Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme Nairobi, Kenya
| | - Peter M Atkinson
- Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK; Geography and Environmental Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK; Institute of Geographic Sciences and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
| | - C Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK; Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Victor A Alegana
- Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya; Geography and Environmental Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK
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27
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Boo G, Darin E, Leasure DR, Dooley CA, Chamberlain HR, Lázár AN, Tschirhart K, Sinai C, Hoff NA, Fuller T, Musene K, Batumbo A, Rimoin AW, Tatem AJ. High-resolution population estimation using household survey data and building footprints. Nat Commun 2022; 13:1330. [PMID: 35288578 PMCID: PMC8921279 DOI: 10.1038/s41467-022-29094-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 02/23/2022] [Indexed: 11/19/2022] Open
Abstract
The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses. A lack of up-to-date population figures may hamper effective decision-making. Here, the authors develop a Bayesian model to estimate population data at high resolution in five provinces of the Democratic Republic of the Congo.
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28
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Pezzulo C, Alegana VA, Christensen A, Bakari O, Tatem AJ. Understanding factors associated with attending secondary school in Tanzania using household survey data. PLoS One 2022; 17:e0263734. [PMID: 35213555 PMCID: PMC8880958 DOI: 10.1371/journal.pone.0263734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 01/25/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Sustainable Development Goal (SDG) 4 aims to ensure inclusive and equitable access for all by 2030, leaving no one behind. One indicator selected to measure progress towards achievement is the participation rate of youth in education (SDG 4.3.1). Here we aim to understand drivers of school attendance using one country in East Africa as an example. METHODS Nationally representative household survey data (2015-16 Tanzania Demographic and Health Survey) were used to explore individual, household and contextual factors associated with secondary school attendance in Tanzania. These included, age, head of household's levels of education, gender, household wealth index and total number of children under five. Contextual factors such as average pupil to qualified teacher ratio and geographic access to school were also tested at cluster level. A two-level random intercept logistic regression model was used in exploring association of these factors with attendance in a multi-level framework. RESULTS Age of household head, educational attainments of either of the head of the household or parent, child characteristics such as gender, were important predictors of secondary school attendance. Being in a richer household and with fewer siblings of lower age (under the age of 5) were associated with increased odds of attendance (OR = 0.91, CI 95%: 0.86; 0.96). Contextual factors were less likely to be associated with secondary school attendance. CONCLUSIONS Individual and household level factors are likely to impact secondary school attendance rates more compared to contextual factors, suggesting an increased focus of interventions at these levels is needed. Future studies should explore the impact of interventions targeting these levels. Policies should ideally promote gender equality in accessing secondary school as well as support those families where the dependency ratio is high. Strategies to reduce poverty will also increase the likelihood of attending school.
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Affiliation(s)
- Carla Pezzulo
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Victor A. Alegana
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
- Population Health Unit, Kenya Medical Research Institute—Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Andrew Christensen
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
- Plan Denmark (PlanBørnefonden), Copenhagen, DK, United Kingdom
| | - Omar Bakari
- Tanzania DataLab (dLab), Dar es Salaam, Tanzania
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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29
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Ge Y, Zhang WB, Liu H, Ruktanonchai CW, Hu M, Wu X, Song Y, Ruktanonchai NW, Yan W, Cleary E, Feng L, Li Z, Yang W, Liu M, Tatem AJ, Wang JF, Lai S. Impacts of worldwide individual non-pharmaceutical interventions on COVID-19 transmission across waves and space. Int J Appl Earth Obs Geoinf 2022; 106:102649. [PMID: 35110979 PMCID: PMC8666325 DOI: 10.1016/j.jag.2021.102649] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 12/06/2021] [Accepted: 12/10/2021] [Indexed: 05/19/2023]
Abstract
Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections and multi-source big data, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America [USA]) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases.
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Affiliation(s)
- Yong Ge
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Wen-Bin Zhang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Haiyan Liu
- Marine Data Center, South Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Corrine W Ruktanonchai
- Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Maogui Hu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Xilin Wu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Yongze Song
- School of Design and the Built Environment, Curtin University, Perth, 6101, Australia
| | - Nick W Ruktanonchai
- Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Wei Yan
- Respiratory Medicine Department, Peking University Third Hospital, Beijing, China
| | - Eimear Cleary
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhongjie Li
- Divisions of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weizhong Yang
- Divisions of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mengxiao Liu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Jin-Feng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Academy of Sciences, Beijing, China
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
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30
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Lai S, Sorichetta A, Steele J, Ruktanonchai CW, Cunningham AD, Rogers G, Koper P, Woods D, Bondarenko M, Ruktanonchai NW, Shi W, Tatem AJ. Global holiday datasets for understanding seasonal human mobility and population dynamics. Sci Data 2022; 9:17. [PMID: 35058466 PMCID: PMC8776767 DOI: 10.1038/s41597-022-01120-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 12/10/2021] [Indexed: 11/17/2022] Open
Abstract
Public and school holidays have important impacts on population mobility and dynamics across multiple spatial and temporal scales, subsequently affecting the transmission dynamics of infectious diseases and many socioeconomic activities. However, worldwide data on public and school holidays for understanding their changes across regions and years have not been assembled into a single, open-source and multitemporal dataset. To address this gap, an open access archive of data on public and school holidays in 2010-2019 across the globe at daily, weekly, and monthly timescales was constructed. Airline passenger volumes across 90 countries from 2010 to 2018 were also assembled to illustrate the usage of the holiday data for understanding the changing spatiotemporal patterns of population movements.
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Affiliation(s)
- Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK.
| | - Alessandro Sorichetta
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Jessica Steele
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Corrine W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Alexander D Cunningham
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Grant Rogers
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Patrycja Koper
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Dorothea Woods
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Maksym Bondarenko
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Nick W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Weifeng Shi
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
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Utazi CE, Pannell O, Aheto JMK, Wigley A, Tejedor-Garavito N, Wunderlich J, Hagedorn B, Hogan D, Tatem AJ. Assessing the characteristics of un- and under-vaccinated children in low- and middle-income countries: A multi-level cross-sectional study. PLOS Glob Public Health 2022; 2:e0000244. [PMID: 36962232 PMCID: PMC10021434 DOI: 10.1371/journal.pgph.0000244] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 02/03/2022] [Indexed: 11/18/2022]
Abstract
Achieving equity in vaccination coverage has been a critical priority within the global health community. Despite increased efforts recently, certain populations still have a high proportion of un- and under-vaccinated children in many low- and middle-income countries (LMICs). These populations are often assumed to reside in remote-rural areas, urban slums and conflict-affected areas. Here, we investigate the effects of these key community-level factors, alongside a wide range of other individual, household and community level factors, on vaccination coverage. Using geospatial datasets, including cross-sectional data from the most recent Demographic and Health Surveys conducted between 2008 and 2018 in nine LMICs, we fitted Bayesian multi-level binary logistic regression models to determine key community-level and other factors significantly associated with non- and under-vaccination. We analyzed the odds of receipt of the first doses of diphtheria-tetanus-pertussis (DTP1) vaccine and measles-containing vaccine (MCV1), and receipt of all three recommended DTP doses (DTP3) independently, in children aged 12-23 months. In bivariate analyses, we found that remoteness increased the odds of non- and under-vaccination in nearly all the study countries. We also found evidence that living in conflict and urban slum areas reduced the odds of vaccination, but not in most cases as expected. However, the odds of vaccination were more likely to be lower in urban slums than formal urban areas. Our multivariate analyses revealed that the key community variables-remoteness, conflict and urban slum-were sometimes associated with non- and under-vaccination, but they were not frequently predictors of these outcomes after controlling for other factors. Individual and household factors such as maternal utilization of health services, maternal education and ethnicity, were more common predictors of vaccination. Reaching the Immunisation Agenda 2030 target of reducing the number of zero-dose children by 50% by 2030 will require country tailored analyses and strategies to identify and reach missed communities with reliable immunisation services.
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Affiliation(s)
- C Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Oliver Pannell
- Flowminder Foundation and WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Justice M K Aheto
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Adelle Wigley
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Natalia Tejedor-Garavito
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | | | - Brittany Hagedorn
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, Washington, WA, United States of America
| | - Dan Hogan
- Gavi, The Vaccine Alliance, Geneva, Switzerland
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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Tan S, Lai S, Fang F, Cao Z, Sai B, Song B, Dai B, Guo S, Liu C, Cai M, Wang T, Wang M, Li J, Chen S, Qin S, Floyd JR, Cao Z, Tan J, Sun X, Zhou T, Zhang W, Tatem AJ, Holme P, Chen X, Lu X. Mobility in China, 2020: a tale of four phases. Natl Sci Rev 2021; 8:nwab148. [PMID: 34876997 PMCID: PMC8645011 DOI: 10.1093/nsr/nwab148] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 08/05/2021] [Accepted: 08/10/2021] [Indexed: 02/05/2023] Open
Abstract
2020 was an unprecedented year, with rapid and drastic changes in human mobility due to the COVID-19 pandemic. To understand the variation in commuting patterns among the Chinese population across stable and unstable periods, we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of population movements in 2020, ranging from the Lunar New Year travel season (chunyun), to the exceptional calm of COVID-19 lockdown, and then to the recovery period. We observed that cross-city movements, which increased substantially in chunyun and then dropped sharply during the lockdown, are primarily dependent on travel distance and the socio-economic development of cities. Following the Lunar New Year holiday, national mobility remained low until mid-February, and COVID-19 interventions delayed more than 72.89 million people returning to large cities. Mobility network analysis revealed clusters of highly connected cities, conforming to the social-economic division of urban agglomerations in China. While the mass migration back to large cities was delayed, smaller cities connected more densely to form new clusters. During the recovery period after travel restrictions were lifted, the netflows of over 55% city pairs reversed in direction compared to before the lockdown. These findings offer the most comprehensive picture of Chinese mobility at fine resolution across various scenarios in China and are of critical importance for decision making regarding future public-health-emergency response, transportation planning and regional economic development, among others.
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Affiliation(s)
- Suoyi Tan
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Fan Fang
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Ziqiang Cao
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Bin Sai
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Bing Song
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Bitao Dai
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Shuhui Guo
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Chuchu Liu
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Mengsi Cai
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Tong Wang
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Mengning Wang
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Jiaxu Li
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
| | - Saran Chen
- School of Mathematics and Big Data, Foshan University, Foshan 510000, China
| | - Shuo Qin
- State Key Laboratory on Blind Signal Processing, Chengdu 610041, China
| | - Jessica R Floyd
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Zhidong Cao
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Jing Tan
- Chinese Evidence-Based Medicine Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Xin Sun
- Chinese Evidence-Based Medicine Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Tao Zhou
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611713, China
| | - Wei Zhang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610047, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Petter Holme
- Tokyo Tech World Hub Research Initiative, Institute of Innovative Research, Tokyo Institute of Technology, Tokyo 226-8503, Japan
| | - Xiaohong Chen
- School of Business, Central South University, Changsha 410083, China
| | - Xin Lu
- College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
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Shepherd HER, Atherden FS, Chan HMT, Loveridge A, Tatem AJ. Domestic and international mobility trends in the United Kingdom during the COVID-19 pandemic: an analysis of facebook data. Int J Health Geogr 2021; 20:46. [PMID: 34863206 PMCID: PMC8643186 DOI: 10.1186/s12942-021-00299-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 11/08/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Since early March 2020, the COVID-19 epidemic across the United Kingdom has led to a range of social distancing policies, which resulted in changes to mobility across different regions. An understanding of how these policies impacted travel patterns over time and at different spatial scales is important for designing effective strategies, future pandemic planning and in providing broader insights on the population geography of the country. Crowd level data on mobile phone usage can be used as a proxy for population mobility patterns and provide a way of quantifying in near-real time the impact of social distancing measures on changes in mobility. METHODS Here we explore patterns of change in densities, domestic and international flows and co-location of Facebook users in the UK from March 2020 to March 2021. RESULTS We find substantial heterogeneities across time and region, with large changes observed compared to pre-pademic patterns. The impacts of periods of lockdown on distances travelled and flow volumes are evident, with each showing variations, but some significant reductions in co-location rates. Clear differences in multiple metrics of mobility are seen in central London compared to the rest of the UK, with each of Scotland, Wales and Northern Ireland showing significant deviations from England at times. Moreover, the impacts of rapid changes in rules on international travel to and from the UK are seen in substantial fluctuations in traveller volumes by destination. CONCLUSIONS While questions remain about the representativeness of the Facebook data, previous studies have shown strong correspondence with census-based data and alternative mobility measures, suggesting that findings here are valuable for guiding strategies.
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Affiliation(s)
- Harry E R Shepherd
- School of Biological Sciences, University of Southampton, Southampton, UK
| | - Florence S Atherden
- Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton, UK
| | | | - Alexandra Loveridge
- Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
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Franklinos LHV, Parrish R, Burns R, Caflisch A, Mallick B, Rahman T, Routsis V, López AS, Tatem AJ, Trigwell R. Key opportunities and challenges for the use of big data in migration research and policy. UCL Open Environ 2021; 3:e027. [PMID: 37228797 PMCID: PMC10171412 DOI: 10.14324/111.444/ucloe.000027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 09/23/2021] [Indexed: 05/27/2023]
Abstract
Migration is one of the defining issues of the 21st century. Better data is required to improve understanding about how and why people are moving, target interventions and support evidence-based migration policy. Big data, defined as large, complex data from diverse sources, is regularly proposed as a solution to help address current gaps in knowledge. The authors participated in a workshop held in London, UK, in July 2019, that brought together experts from the United Nations (UN), humanitarian non-governmental organisations (NGOs), policy and academia to develop a better understanding of how big data could be used for migration research and policy. We identified six key areas regarding the application of big data in migration research and policy: accessing and utilising data; integrating data sources and knowledge; understanding environmental drivers of migration; improving healthcare access for migrant populations; ethical and security concerns around the use of big data; and addressing political narratives. We advocate the need for careful consideration of the challenges faced by the use of big data, as well as increased cross-disciplinary collaborations to advance the use of big data in migration research whilst safeguarding vulnerable migrant communities.
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Affiliation(s)
- Lydia H. V. Franklinos
- Institute for Global Health, University College London, London, UK
- Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Rebecca Parrish
- Institute for Global Health, University College London, London, UK
- Institute of Environment, Health and Societies, Brunel University, London, UK
| | - Rachel Burns
- Centre of Public Health Data Science, Institute of Health Informatics, University College London, London, UK
| | - Andrea Caflisch
- United Nations’ Displacement Tracking Matrix, International Organization for Migration, International Organization for Migration, Juba, South Sudan
| | - Bishawjit Mallick
- CU Population Center, Institute of Behavioral Science, University of Colorado Boulder Campus, Boulder, CO, USA
- Faculty of Environmental Sciences, Technische Universität Dresden, Dresden, Germany
| | - Taifur Rahman
- Health Management BD Foundation, Sector 6, Uttara, Dhaka, Bangladesh
- Adjunct Faculty, Department of Public Health, North South University, Dhaka, Bangladesh
| | - Vasileios Routsis
- Department of Information Studies, University College London, London, UK
| | - Ana Sebastián López
- GMV Innovating Solutions Ltd, HQ Building, Thomson Avenue, Harwell Campus, Didcot, UK
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Robert Trigwell
- United Nations’ Displacement Tracking Matrix, International Organization for Migration, United Nations, London, UK
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Hu M, Wang J, Lin H, Ruktanonchai CW, Xu C, Meng B, Zhang X, Carioli A, Feng Y, Yin Q, Floyd JR, Ruktanonchai NW, Li Z, Yang W, Tatem AJ, Lai S. Risk of SARS-CoV-2 Transmission among Air Passengers in China. Clin Infect Dis 2021; 75:e234-e240. [PMID: 34549275 DOI: 10.1093/cid/ciab836] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Modern transportation plays a key role in the spread of SARS-CoV-2 and new variants. However, little is known about the exact transmission risk of the virus on airplanes. METHODS Using the itinerary and epidemiological data of COVID-19 cases and close contacts on domestic airplanes departing from Wuhan city in China before the lockdown on January 23, 2020, we estimated the upper and lower bounds of overall transmission risk of COVID-19 among travellers. RESULTS 175 index cases were identified among 5797 passengers on 177 airplanes. The upper and lower attack rates (ARs) of a seat were 0.60% (34/5622, 95%CI 0.43%-0.84%) and 0.33% (18/5400, 95%CI 0.21%-0.53%), respectively. In the upper- and lower-bound risk estimates, each index case infected 0.19 (SD 0.45) and 0.10 (SD 0.32) cases respectively. The seats immediately adjacent to the index cases had an AR of 9.2% (95%CI 5.7%-14.4%), with a relative risk 27.8 (95%CI 14.4-53.7) compared to other seats in the upper limit estimation. The middle seat had the highest AR (0.7%, 95%CI 0.4%-1.2%). The upper-bound AR increased from 0.7% (95%CI 0.5%-1.0%) to 1.2% (95%CI 0.4%-3.3%) when the co-travel time increased from 2.0 hours to 3.3 hours. CONCLUSIONS The ARs among travellers varied by seat distance from the index case and joint travel time, but the variation was not significant between the types of aircraft. The overall risk of SARS-CoV-2 transmission during domestic travel on planes was relatively low. These findings can improve our understanding of COVID-19 spread during travel and inform response efforts in the pandemic.
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Affiliation(s)
- Maogui Hu
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Jinfeng Wang
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Hui Lin
- China Academy of Electronics and Information Technology, Beijing, China
| | - Corrine W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Chengdong Xu
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Bin Meng
- Beijing Union University, Beijing, China
| | - Xin Zhang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Alessandra Carioli
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Yuqing Feng
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Qian Yin
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Jessica R Floyd
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Nick W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Zhongjie Li
- Divisions of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weizhong Yang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
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Meredith HR, Giles JR, Perez-Saez J, Mande T, Rinaldo A, Mutembo S, Kabalo EN, Makungo K, Buckee CO, Tatem AJ, Metcalf CJE, Wesolowski A. Characterizing human mobility patterns in rural settings of sub-Saharan Africa. eLife 2021; 10:e68441. [PMID: 34533456 PMCID: PMC8448534 DOI: 10.7554/elife.68441] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 08/21/2021] [Indexed: 11/27/2022] Open
Abstract
Human mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When mobility data are limited, spatial interaction models have been widely used to estimate human travel, but have not been extensively validated in low- and middle-income settings. Geographic, sociodemographic, and infrastructure differences may impact the ability for models to capture these patterns, particularly in rural settings. Here, we analyzed mobility patterns inferred from mobile phone data in four Sub-Saharan African countries to investigate the ability for variants on gravity and radiation models to estimate travel. Adjusting the gravity model such that parameters were fit to different trip types, including travel between more or less populated areas and/or different regions, improved model fit in all four countries. This suggests that alternative models may be more useful in these settings and better able to capture the range of mobility patterns observed.
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Affiliation(s)
- Hannah R Meredith
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
| | - John R Giles
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
| | - Javier Perez-Saez
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
| | - Théophile Mande
- Bureau d'Etudes Scientifiques et Techniques - Eau, Energie, Environnement (BEST-3E), Ouagadougou, Burkina Faso
| | - Andrea Rinaldo
- Dipartimento di Ingegneria Civile Edile ed Ambientale, Università di Padova, Padova, Italy
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Simon Mutembo
- Department of International Health, International Vaccine Access Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
- Macha Research Trust, Choma, Zambia
| | - Elliot N Kabalo
- Zambia Information and Communications Technology Authority, Lusaka, Zambia
| | | | - Caroline O Buckee
- Department of Epidemiology and the Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, United States
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology and the Princeton School of Public and International Affairs, Princeton University, Princeton, United States
| | - Amy Wesolowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
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37
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Nilsen K, Tejedor-Garavito N, Leasure DR, Utazi CE, Ruktanonchai CW, Wigley AS, Dooley CA, Matthews Z, Tatem AJ. A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators. BMC Health Serv Res 2021; 21:370. [PMID: 34511089 PMCID: PMC8436450 DOI: 10.1186/s12913-021-06370-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 04/09/2021] [Indexed: 01/05/2023] Open
Abstract
Background Household survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples. Methods We constructed indicators on the percentage of children one year old for diphtheria, pertussis and tetanus vaccine dose 3 (DTP3) and measles vaccine dose (MCV1) in Zambia and Nigeria at district levels. For the numerators, information on vaccines doses was obtained from each country’s respective DHMIS. For the denominators, the number of children was obtained from 3 different sources including national population projections and aggregated gridded estimates derived using top-down and bottom-up geospatial methods. Results In Zambia, vaccination estimates utilising the bottom-up approach to population estimation substantially reduced the number of districts with > 100% coverage of DTP3 and MCV1 compared to estimates using population projection and the top-down method. In Nigeria, results were mixed with bottom-up estimates having a higher number of districts > 100% and estimates using population projections performing better particularly in the South. Conclusions Gridded demographic data utilising traditional and novel data sources obtained from remote sensing offer new potential in the absence of up to date census information in the estimation of RMNCAH indicators. However, the usefulness of gridded demographic data is dependent on several factors including the availability and detail of input data. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-021-06370-y.
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Affiliation(s)
- Kristine Nilsen
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
| | - Natalia Tejedor-Garavito
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Douglas R Leasure
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - C Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Corrine W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Adelle S Wigley
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Claire A Dooley
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Zoe Matthews
- Department of Social Statistics and Demography, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
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38
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Giles JR, Cummings DAT, Grenfell BT, Tatem AJ, zu Erbach-Schoenberg E, Metcalf CJE, Wesolowski A. Trip duration drives shift in travel network structure with implications for the predictability of spatial disease spread. PLoS Comput Biol 2021; 17:e1009127. [PMID: 34375331 PMCID: PMC8378725 DOI: 10.1371/journal.pcbi.1009127] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 08/20/2021] [Accepted: 05/28/2021] [Indexed: 11/19/2022] Open
Abstract
Human travel is one of the primary drivers of infectious disease spread. Models of travel are often used that assume the amount of travel to a specific destination decreases as cost of travel increases with higher travel volumes to more populated destinations. Trip duration, the length of time spent in a destination, can also impact travel patterns. We investigated the spatial patterns of travel conditioned on trip duration and find distinct differences between short and long duration trips. In short-trip duration travel networks, trips are skewed towards urban destinations, compared with long-trip duration networks where travel is more evenly spread among locations. Using gravity models to inform connectivity patterns in simulations of disease transmission, we show that pathogens with shorter generation times exhibit initial patterns of spatial propagation that are more predictable among urban locations. Further, pathogens with a longer generation time have more diffusive patterns of spatial spread reflecting more unpredictable disease dynamics. During an epidemic of an infectious pathogen, cases of disease can be imported to new locations when people travel. The amount of time that an infected person spends in a destination (trip duration) determines how likely they are to infect others while travelling. In this study, we analyzed travel data and found specific spatial patterns in trip duration, where short-duration trips are more common between urban destinations and long-duration trips are evenly spread out among locations. To show how this spatial pattern impacts the spread of infectious diseases, we used data-driven models and simulations to show that pathogens with shorter generation times have patterns of spatial spread that are more predictable among urban locations. However, pathogens with longer generation times tend to spread along the long-duration travel networks that are more evenly distributed among locations giving them more unpredictable disease dynamics.
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Affiliation(s)
- John R. Giles
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- * E-mail:
| | - Derek A. T. Cummings
- Department of Biology and the Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Bryan T. Grenfell
- Department of Ecology and Evolutionary Biology and the Princeton School of Public and International Affairs, Princeton University, Princeton, New Jersey, United States of America
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | | | - CJE Metcalf
- Department of Ecology and Evolutionary Biology and the Princeton School of Public and International Affairs, Princeton University, Princeton, New Jersey, United States of America
| | - Amy Wesolowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
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Ruktanonchai CW, Lai S, Utazi CE, Cunningham AD, Koper P, Rogers GE, Ruktanonchai NW, Sadilek A, Woods D, Tatem AJ, Steele JE, Sorichetta A. Practical geospatial and sociodemographic predictors of human mobility. Sci Rep 2021; 11:15389. [PMID: 34321509 PMCID: PMC8319369 DOI: 10.1038/s41598-021-94683-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 07/13/2021] [Indexed: 11/08/2022] Open
Abstract
Understanding seasonal human mobility at subnational scales has important implications across sciences, from urban planning efforts to disease modelling and control. Assessing how, when, and where populations move over the course of the year, however, requires spatially and temporally resolved datasets spanning large periods of time, which can be rare, contain sensitive information, or may be proprietary. Here, we aim to explore how a set of broadly available covariates can describe typical seasonal subnational mobility in Kenya pre-COVID-19, therefore enabling better modelling of seasonal mobility across low- and middle-income country (LMIC) settings in non-pandemic settings. To do this, we used the Google Aggregated Mobility Research Dataset, containing anonymized mobility flows aggregated over users who have turned on the Location History setting, which is off by default. We combined this with socioeconomic and geospatial covariates from 2018 to 2019 to quantify seasonal changes in domestic and international mobility patterns across years. We undertook a spatiotemporal analysis within a Bayesian framework to identify relevant geospatial and socioeconomic covariates explaining human movement patterns, while accounting for spatial and temporal autocorrelations. Typical pre-pandemic mobility patterns in Kenya mostly consisted of shorter, within-county trips, followed by longer domestic travel between counties and international travel, which is important in establishing how mobility patterns changed post-pandemic. Mobility peaked in August and December, closely corresponding to school holiday seasons, which was found to be an important predictor in our model. We further found that socioeconomic variables including urbanicity, poverty, and female education strongly explained mobility patterns, in addition to geospatial covariates such as accessibility to major population centres and temperature. These findings derived from novel data sources elucidate broad spatiotemporal patterns of how populations move within and beyond Kenya, and can be easily generalized to other LMIC settings before the COVID-19 pandemic. Understanding such pre-pandemic mobility patterns provides a crucial baseline to interpret both how these patterns have changed as a result of the pandemic, as well as whether human mobility patterns have been permanently altered once the pandemic subsides. Our findings outline key correlates of mobility using broadly available covariates, alleviating the data bottlenecks of highly sensitive and proprietary mobile phone datasets, which many researchers do not have access to. These results further provide novel insight on monitoring mobility proxies in the context of disease surveillance and control efforts through LMIC settings.
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Affiliation(s)
- Corrine W Ruktanonchai
- Population Health Sciences, College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, USA.
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Chigozie E Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Alex D Cunningham
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Patrycja Koper
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Grant E Rogers
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Nick W Ruktanonchai
- Population Health Sciences, College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, USA
| | | | - Dorothea Woods
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Jessica E Steele
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Alessandro Sorichetta
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
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40
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Lemey P, Ruktanonchai N, Hong SL, Colizza V, Poletto C, Van den Broeck F, Gill MS, Ji X, Levasseur A, Oude Munnink BB, Koopmans M, Sadilek A, Lai S, Tatem AJ, Baele G, Suchard MA, Dellicour S. Untangling introductions and persistence in COVID-19 resurgence in Europe. Nature 2021; 595:713-717. [PMID: 34192736 PMCID: PMC8324533 DOI: 10.1038/s41586-021-03754-2] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/22/2021] [Indexed: 11/09/2022]
Abstract
After the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting in late summer 2020 that was deadlier and more difficult to contain1. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave2. Here we build a phylogeographical model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the resurgence of COVID-19 in Europe. We inform this model using genomic, mobility and epidemiological data from 10 European countries and estimate that in many countries more than half of the lineages circulating in late summer resulted from new introductions since 15 June 2020. The success in onward transmission of newly introduced lineages was negatively associated with the local incidence of COVID-19 during this period. The pervasive spread of variants in summer 2020 highlights the threat of viral dissemination when restrictions are lifted, and this needs to be carefully considered in strategies to control the current spread of variants that are more transmissible and/or evade immunity. Our findings indicate that more effective and coordinated measures are required to contain the spread through cross-border travel even as vaccination is reducing disease burden.
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Affiliation(s)
- Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium.
- Global Virus Network (GVN), Baltimore, MD, USA.
| | - Nick Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Samuel L Hong
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, Paris, France
| | - Chiara Poletto
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, Paris, France
| | - Frederik Van den Broeck
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA, USA
| | - Anthony Levasseur
- UMR MEPHI (Microbes, Evolution, Phylogeny and Infections), Aix-Marseille Université (AMU) and Institut Universitaire de France (IUF), Marseille, France
| | - Bas B Oude Munnink
- Department of Viroscience, WHO Collaborating Centre for Arbovirus and Viral Hemorrhagic Fever Reference and Research, Erasmus MC, Rotterdam, The Netherlands
| | - Marion Koopmans
- Department of Viroscience, WHO Collaborating Centre for Arbovirus and Viral Hemorrhagic Fever Reference and Research, Erasmus MC, Rotterdam, The Netherlands
| | | | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium.
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium.
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41
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Lai S, Ruktanonchai NW, Carioli A, Ruktanonchai CW, Floyd JR, Prosper O, Zhang C, Du X, Yang W, Tatem AJ. Assessing the Effect of Global Travel and Contact Restrictions on Mitigating the COVID-19 Pandemic. Engineering (Beijing) 2021; 7:914-923. [PMID: 33972889 PMCID: PMC8099556 DOI: 10.1016/j.eng.2021.03.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/01/2021] [Accepted: 03/23/2021] [Indexed: 05/04/2023]
Abstract
Travel restrictions and physical distancing have been implemented across the world to mitigate the coronavirus disease 2019 (COVID-19) pandemic, but studies are needed to understand their effectiveness across regions and time. Based on the population mobility metrics derived from mobile phone geolocation data across 135 countries or territories during the first wave of the pandemic in 2020, we built a metapopulation epidemiological model to measure the effect of travel and contact restrictions on containing COVID-19 outbreaks across regions. We found that if these interventions had not been deployed, the cumulative number of cases could have shown a 97-fold (interquartile range 79-116) increase, as of May 31, 2020. However, their effectiveness depended upon the timing, duration, and intensity of the interventions, with variations in case severity seen across populations, regions, and seasons. Additionally, before effective vaccines are widely available and herd immunity is achieved, our results emphasize that a certain degree of physical distancing at the relaxation of the intervention stage will likely be needed to avoid rapid resurgences and subsequent lockdowns.
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Affiliation(s)
- Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Nick W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA 24061, USA
| | - Alessandra Carioli
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Corrine W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Jessica R Floyd
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Olivia Prosper
- Department of Mathematics, University of Tennessee, Knoxville, TN 37996, USA
| | - Chi Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 510275, China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 510275, China
| | - Weizhong Yang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
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42
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Pezzulo C, Nilsen K, Carioli A, Tejedor-Garavito N, Hanspal SE, Hilber T, James WHM, Ruktanonchai CW, Alegana V, Sorichetta A, Wigley AS, Hornby GM, Matthews Z, Tatem AJ. Geographical distribution of fertility rates in 70 low-income, lower-middle-income, and upper-middle-income countries, 2010-16: a subnational analysis of cross-sectional surveys. Lancet Glob Health 2021; 9:e802-e812. [PMID: 34019836 PMCID: PMC8149299 DOI: 10.1016/s2214-109x(21)00082-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 02/10/2021] [Accepted: 02/11/2021] [Indexed: 12/03/2022]
Abstract
BACKGROUND Understanding subnational variation in age-specific fertility rates (ASFRs) and total fertility rates (TFRs), and geographical clustering of high fertility and its determinants in low-income and middle-income countries, is increasingly needed for geographical targeting and prioritising of policy. We aimed to identify variation in fertility rates, to describe patterns of key selected fertility determinants in areas of high fertility. METHODS We did a subnational analysis of ASFRs and TFRs from the most recent publicly available and nationally representative cross-sectional Demographic and Health Surveys and Multiple Indicator Cluster Surveys collected between 2010 and 2016 for 70 low-income, lower-middle-income, and upper-middle-income countries, across 932 administrative units. We assessed the degree of global spatial autocorrelation by using Moran's I statistic and did a spatial cluster analysis using the Getis-Ord Gi* local statistic to examine the geographical clustering of fertility and key selected fertility determinants. Descriptive analysis was used to investigate the distribution of ASFRs and of selected determinants in each cluster. FINDINGS TFR varied from below replacement (2·1 children per women) in 36 of the 932 subnational regions (mainly located in India, Myanmar, Colombia, and Armenia), to rates of 8 and higher in 14 subnational regions, located in sub-Saharan Africa and Afghanistan. Areas with high-fertility clusters were mostly associated with areas of low prevalence of women with secondary or higher education, low use of contraception, and high unmet needs for family planning, although exceptions existed. INTERPRETATION Substantial within-country variation in the distribution of fertility rates highlights the need for tailored programmes and strategies in high-fertility cluster areas to increase the use of contraception and access to secondary education, and to reduce unmet need for family planning. FUNDING Wellcome Trust, the UK Foreign, Commonwealth and Development Office, and the Bill & Melinda Gates Foundation.
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Affiliation(s)
- Carla Pezzulo
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK.
| | - Kristine Nilsen
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Alessandra Carioli
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | | | - Sophie E Hanspal
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Theodor Hilber
- Department of Earth Sciences Centre for Development Research, Freie Universität Berlin, Germany
| | - William H M James
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK; School of Geography, and Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
| | - Corrine W Ruktanonchai
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK; Department of Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Victor Alegana
- Population Health Unit, Kenya Medical Research Institute, Wellcome Trust Research Programme, Nairobi, Kenya; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Alessandro Sorichetta
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Adelle S Wigley
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Graeme M Hornby
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK; GeoData, University of Southampton, Southampton, UK
| | - Zoe Matthews
- Division of Social Statistics, and Demography and Centre for Global Health, Population, Poverty and Policy, University of Southampton, Southampton, UK
| | - Andrew J Tatem
- WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
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43
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Rice BL, Annapragada A, Baker RE, Bruijning M, Dotse-Gborgbortsi W, Mensah K, Miller IF, Motaze NV, Raherinandrasana A, Rajeev M, Rakotonirina J, Ramiadantsoa T, Rasambainarivo F, Yu W, Grenfell BT, Tatem AJ, Metcalf CJE. Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa. Nat Med 2021; 27:447-453. [PMID: 33531710 PMCID: PMC8590469 DOI: 10.1038/s41591-021-01234-8] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 01/11/2021] [Indexed: 12/27/2022]
Abstract
A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments1, younger populations2-4) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.
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Affiliation(s)
- Benjamin L Rice
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
- Madagascar Health and Environmental Research, Maroantsetra, Madagascar.
| | | | - Rachel E Baker
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Princeton Environmental Institute, Princeton University, Princeton, NJ, USA
| | - Marjolein Bruijning
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | | | - Keitly Mensah
- Centre Population et Développement (CEPED), Institut de Recherche pour le Développement (IRD) and Université de Paris, Inserm ERL 1244, Paris, France
| | - Ian F Miller
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Nkengafac Villyen Motaze
- Centre for Vaccines and Immunology, National Institute for Comnmunicable Diseases, National Health Laboratory Service, Johannesburg, South Africa
- Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Antso Raherinandrasana
- Faculty of Medicine, University of Antananarivo, Antananarivo, Madagascar
- Teaching Hospital of Care and Public Health Analakely, Antananarivo, Madagascar
| | - Malavika Rajeev
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Julio Rakotonirina
- Faculty of Medicine, University of Antananarivo, Antananarivo, Madagascar
- Teaching Hospital of Care and Public Health Analakely, Antananarivo, Madagascar
| | - Tanjona Ramiadantsoa
- Department of Life Science, University of Fianarantsoa, Fianarantsoa, Madagascar
- Department of Mathematics, University of Fianarantsoa, Fianarantsoa, Madagascar
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA
| | - Fidisoa Rasambainarivo
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Mahaliana Labs SARL, Antananarivo, Madagascar
| | - Weiyu Yu
- School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Princeton School of Public and International Affairs, Princeton University, Princeton, NJ, USA
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44
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Jochem WC, Tatem AJ. Tools for mapping multi-scale settlement patterns of building footprints: An introduction to the R package foot. PLoS One 2021; 16:e0247535. [PMID: 33630905 PMCID: PMC7906393 DOI: 10.1371/journal.pone.0247535] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/08/2021] [Indexed: 11/19/2022] Open
Abstract
Spatial datasets of building footprint polygons are becoming more widely available and accessible for many areas in the world. These datasets are important inputs for a range of different analyses, such as understanding the development of cities, identifying areas at risk of disasters, and mapping the distribution of populations. The growth of high spatial resolution imagery and computing power is enabling automated procedures to extract and map building footprints for whole countries. These advances are enabling coverage of building footprint datasets for low and middle income countries which might lack other data on urban land uses. While spatially detailed, many building footprints lack information on structure type, local zoning, or land use, limiting their application. However, morphology metrics can be used to describe characteristics of size, shape, spacing, orientation and patterns of the structures and extract additional information which can be correlated with different structure and settlement types or neighbourhoods. We introduce the foot package, a new set of open-source tools in a flexible R package for calculating morphology metrics for building footprints and summarising them in different spatial scales and spatial representations. In particular our tools can create gridded (or raster) representations of morphology summary metrics which have not been widely supported previously. We demonstrate the tools by creating gridded morphology metrics from all building footprints in England, Scotland and Wales, and then use those layers in an unsupervised cluster analysis to derive a pattern-based settlement typology. We compare our mapped settlement types with two existing settlement classifications. The results suggest that building patterns can help distinguish different urban and rural types. However, intra-urban differences were not well-predicted by building morphology alone. More broadly, though, this case study demonstrates the potential of mapping settlement patterns in the absence of a housing census or other urban planning data.
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Affiliation(s)
- Warren C. Jochem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
- * E-mail:
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
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45
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Huang B, Wang J, Cai J, Yao S, Chan PKS, Tam THW, Hong YY, Ruktanonchai CW, Carioli A, Floyd JR, Ruktanonchai NW, Yang W, Li Z, Tatem AJ, Lai S. Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities. Nat Hum Behav 2021; 5:695-705. [PMID: 33603201 DOI: 10.1038/s41562-021-01063-2] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Accepted: 01/27/2021] [Indexed: 12/13/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges to the formulation of preventive interventions, particularly since the effects of physical distancing measures and upcoming vaccines on reducing susceptible social contacts and eventually halting transmission remain unclear. Here, using anonymized mobile geolocation data in China, we devise a mobility-associated social contact index to quantify the impact of both physical distancing and vaccination measures in a unified way. Building on this index, our epidemiological model reveals that vaccination combined with physical distancing can contain resurgences without relying on stay-at-home restrictions, whereas a gradual vaccination process alone cannot achieve this. Further, for cities with medium population density, vaccination can reduce the duration of physical distancing by 36% to 78%, whereas for cities with high population density, infection numbers can be well-controlled through moderate physical distancing. These findings improve our understanding of the joint effects of vaccination and physical distancing with respect to a city's population density and social contact patterns.
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Affiliation(s)
- Bo Huang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR. .,Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR. .,Department of Sociology and Center for Population Research, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR.
| | - Jionghua Wang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR
| | | | - Shiqi Yao
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Paul Kay Sheung Chan
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR. .,Stanley Ho Centre for Emerging Infectious Diseases, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR.
| | - Tony Hong-Wing Tam
- Department of Sociology and Center for Population Research, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Ying-Yi Hong
- Department of Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR
| | - Corrine W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Alessandra Carioli
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Jessica R Floyd
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Nick W Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Weizhong Yang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhongjie Li
- Division of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,School of Public Health, Fudan University, Shanghai, China
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46
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Hu M, Lin H, Wang J, Xu C, Tatem AJ, Meng B, Zhang X, Liu Y, Wang P, Wu G, Xie H, Lai S. Risk of Coronavirus Disease 2019 Transmission in Train Passengers: an Epidemiological and Modeling Study. Clin Infect Dis 2021; 72:604-610. [PMID: 32726405 PMCID: PMC7454391 DOI: 10.1093/cid/ciaa1057] [Citation(s) in RCA: 137] [Impact Index Per Article: 45.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Accepted: 07/21/2020] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Train travel is a common mode of public transport across the globe; however, the risk of coronavirus disease 2019 (COVID-19) transmission among individual train passengers remains unclear. METHODS We quantified the transmission risk of COVID-19 on high-speed train passengers using data from 2334 index patients and 72 093 close contacts who had co-travel times of 0-8 hours from 19 December 2019 through 6 March 2020 in China. We analyzed the spatial and temporal distribution of COVID-19 transmission among train passengers to elucidate the associations between infection, spatial distance, and co-travel time. RESULTS The attack rate in train passengers on seats within a distance of 3 rows and 5 columns of the index patient varied from 0 to 10.3% (95% confidence interval [CI], 5.3%-19.0%), with a mean of 0.32% (95% CI, .29%-.37%). Passengers in seats on the same row (including the adjacent passengers to the index patient) as the index patient had an average attack rate of 1.5% (95% CI, 1.3%-1.8%), higher than that in other rows (0.14% [95% CI, .11%-.17%]), with a relative risk (RR) of 11.2 (95% CI, 8.6-14.6). Travelers adjacent to the index patient had the highest attack rate (3.5% [95% CI, 2.9%-4.3%]) of COVID-19 infection (RR, 18.0 [95% CI, 13.9-23.4]) among all seats. The attack rate decreased with increasing distance, but increased with increasing co-travel time. The attack rate increased on average by 0.15% (P = .005) per hour of co-travel; for passengers in adjacent seats, this increase was 1.3% (P = .008), the highest among all seats considered. CONCLUSIONS COVID-19 has a high transmission risk among train passengers, but this risk shows significant differences with co-travel time and seat location. During disease outbreaks, when traveling on public transportation in confined spaces such as trains, measures should be taken to reduce the risk of transmission, including increasing seat distance, reducing passenger density, and use of personal hygiene protection.
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Affiliation(s)
- Maogui Hu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Hui Lin
- China Academy of Electronics and Information Technology, Beijing, China
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Chengdong Xu
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom
| | - Bin Meng
- Beijing Union University, Beijing, China
| | - Xin Zhang
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Yifeng Liu
- China Academy of Electronics and Information Technology, Beijing, China
| | - Pengda Wang
- China Academy of Electronics and Information Technology, Beijing, China
| | - Guizhen Wu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Haiyong Xie
- China Academy of Electronics and Information Technology, Beijing, China.,University of Science and Technology of China, Hefei, China
| | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom.,School of Public Health, Fudan University, Shanghai, China
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47
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Lemey P, Ruktanonchai N, Hong SL, Colizza V, Poletto C, Van den Broeck F, Gill MS, Ji X, Levasseur A, Sadilek A, Lai S, Tatem AJ, Baele G, Suchard MA, Dellicour S. SARS-CoV-2 European resurgence foretold: interplay of introductions and persistence by leveraging genomic and mobility data. Res Sq 2021:rs.3.rs-208849. [PMID: 33594355 PMCID: PMC7885927 DOI: 10.21203/rs.3.rs-208849/v1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Following the first wave of SARS-CoV-2 infections in spring 2020, Europe experienced a resurgence of the virus starting late summer that was deadlier and more difficult to contain. Relaxed intervention measures and summer travel have been implicated as drivers of the second wave. Here, we build a phylogeographic model to evaluate how newly introduced lineages, as opposed to the rekindling of persistent lineages, contributed to the COVID-19 resurgence in Europe. We inform this model using genomic, mobility and epidemiological data from 10 West European countries and estimate that in many countries more than 50% of the lineages circulating in late summer resulted from new introductions since June 15th. The success in onwards transmission of these lineages is predicted by SARS-CoV-2 incidence during this period. Relatively early introductions from Spain into the United Kingdom contributed to the successful spread of the 20A.EU1/B.1.177 variant. The pervasive spread of variants that have not been associated with an advantage in transmissibility highlights the threat of novel variants of concern that emerged more recently and have been disseminated by holiday travel. Our findings indicate that more effective and coordinated measures are required to contain spread through cross-border travel.
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Affiliation(s)
- Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Global Virus Network (GVN), Baltimore, MD, USA
| | - Nick Ruktanonchai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
- Population Health Sciences, Virginia Tech, Blacksburg, VA, USA
| | - Samuel L Hong
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012 Paris, France
| | - Chiara Poletto
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012 Paris, France
| | - Frederik Van den Broeck
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Mandev S Gill
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Xiang Ji
- Department of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA, USA
| | - Anthony Levasseur
- Microbes, Evolution, Phylogeny and Infection, Aix-Marseille Université and Marseille Institut Universitaire de France, Marseille, France
| | | | - Shengjie Lai
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Marc A Suchard
- Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 av. FD Roosevelt, 1050 Bruxelles, Belgium
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48
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Utazi CE, Nilsen K, Pannell O, Dotse-Gborgbortsi W, Tatem AJ. District-level estimation of vaccination coverage: Discrete vs continuous spatial models. Stat Med 2021; 40:2197-2211. [PMID: 33540473 PMCID: PMC8638675 DOI: 10.1002/sim.8897] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 01/10/2021] [Accepted: 01/15/2021] [Indexed: 01/29/2023]
Abstract
Health and development indicators (HDIs) such as vaccination coverage are regularly measured in many low‐ and middle‐income countries using household surveys, often due to the unreliability or incompleteness of routine data collection systems. Recently, the development of model‐based approaches for producing subnational estimates of HDIs using survey data, particularly cluster‐level data, has been an active area of research. This is mostly driven by the increasing demand for estimates at certain administrative levels, for example, districts, at which many development goals are set and evaluated. In this study, we explore spatial modeling approaches for producing district‐level estimates of vaccination coverage. Specifically, we compare discrete spatial smoothing models which directly model district‐level data with continuous Gaussian process (GP) models that utilize geolocated cluster‐level data. We adopt a fully Bayesian framework, implemented using the INLA and SPDE approaches. We compare the predictive performance of the models by analyzing vaccination coverage using data from two Demographic and Health Surveys (DHS), namely the 2014 Kenya DHS and the 2015‐16 Malawi DHS. We find that the continuous GP models performed well, offering a credible alternative to traditional discrete spatial smoothing models. Our analysis also revealed that accounting for between‐cluster variation in the continuous GP models did not have any real effect on the district‐level estimates. Our results provide guidance to practitioners on the reliability of these model‐based approaches for producing estimates of vaccination coverage and other HDIs.
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Affiliation(s)
- C Edson Utazi
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.,Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, UK
| | - Kristine Nilsen
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | - Oliver Pannell
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
| | | | - Andrew J Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
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49
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Cutts FT, Ferrari MJ, Krause LK, Tatem AJ, Mosser JF. Vaccination strategies for measles control and elimination: time to strengthen local initiatives. BMC Med 2021; 19:2. [PMID: 33397366 PMCID: PMC7781821 DOI: 10.1186/s12916-020-01843-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 11/05/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Through a combination of strong routine immunization (RI), strategic supplemental immunization activities (SIA) and robust surveillance, numerous countries have been able to approach or achieve measles elimination. The fragility of these achievements has been shown, however, by the resurgence of measles since 2016. We describe trends in routine measles vaccine coverage at national and district level, SIA performance and demographic changes in the three regions with the highest measles burden. FINDINGS WHO-UNICEF estimates of immunization coverage show that global coverage of the first dose of measles vaccine has stabilized at 85% from 2015 to 19. In 2000, 17 countries in the WHO African and Eastern Mediterranean regions had measles vaccine coverage below 50%, and although all increased coverage by 2019, at a median of 60%, it remained far below levels needed for elimination. Geospatial estimates show many low coverage districts across Africa and much of the Eastern Mediterranean and southeast Asian regions. A large proportion of children unvaccinated for MCV live in conflict-affected areas with remote rural areas and some urban areas also at risk. Countries with low RI coverage use SIAs frequently, yet the ideal timing and target age range for SIAs vary within countries, and the impact of SIAs has often been mitigated by delays or disruptions. SIAs have not been sufficient to achieve or sustain measles elimination in the countries with weakest routine systems. Demographic changes also affect measles transmission, and their variation between and within countries should be incorporated into strategic planning. CONCLUSIONS Rebuilding services after the COVID-19 pandemic provides a need and an opportunity to increase community engagement in planning and monitoring services. A broader suite of interventions is needed beyond SIAs. Improved methods for tracking coverage at the individual and community level are needed together with enhanced surveillance. Decision-making needs to be decentralized to develop locally-driven, sustainable strategies for measles control and elimination.
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Affiliation(s)
- F T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
| | - M J Ferrari
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA
| | - L K Krause
- Vaccine Delivery, Global Development, The Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - A J Tatem
- WorldPop, Department of Geography and Environmental Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK
| | - J F Mosser
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98121, USA
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50
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Nieves JJ, Bondarenko M, Kerr D, Ves N, Yetman G, Sinha P, Clarke DJ, Sorichetta A, Stevens FR, Gaughan AE, Tatem AJ. Measuring the contribution of built-settlement data to global population mapping. Soc Sci Humanit Open 2021; 3:100102. [PMID: 33889839 PMCID: PMC8041065 DOI: 10.1016/j.ssaho.2020.100102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 12/11/2020] [Accepted: 12/20/2020] [Indexed: 11/24/2022]
Abstract
Top-down population modelling has gained applied prominence in public health, planning, and sustainability applications at the global scale. These top-down population modelling methods often rely on remote-sensing (RS) derived representation of the built-environment and settlements as key predictive covariates. While these RS-derived data, which are global in extent, have become more advanced and more available, gaps in spatial and temporal coverage remain. These gaps have prompted the interpolation of the built-environment and settlements, but the utility of such interpolated data in further population modelling applications has garnered little research. Thus, our objective was to determine the utility of modelled built-settlement extents in a top-down population modelling application. Here we take modelled global built-settlement extents between 2000 and 2012, created using a spatio-temporal disaggregation of observed settlement growth. We then demonstrate the applied utility of such annually modelled settlement data within the application of annually modelling population, using random forest informed dasymetric disaggregations, across 172 countries and a 13-year period. We demonstrate that the modelled built-settlement data are consistently the 2nd most important covariate in predicting population density, behind annual lights at night, across the globe and across the study period. Further, we demonstrate that this modelled built-settlement data often provides more information than current annually available RS-derived data and last observed built-settlement extents.
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Affiliation(s)
- Jeremiah J. Nieves
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Maksym Bondarenko
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - David Kerr
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Nikolas Ves
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Greg Yetman
- Center for International Earth Science Information Network (CIESIN), Columbia University, Palisades, NY, USA
| | - Parmanand Sinha
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
- Department of Geography and Geosciences, University of Louisville, Kentucky, USA
| | - Donna J. Clarke
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Alessandro Sorichetta
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
| | - Forrest R. Stevens
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
- Department of Geography and Geosciences, University of Louisville, Kentucky, USA
| | - Andrea E. Gaughan
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
- Department of Geography and Geosciences, University of Louisville, Kentucky, USA
| | - Andrew J. Tatem
- WorldPop, School of Geography and Environmental Science, University of Southampton, UK
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