1
|
Ali W, Overton CE, Wilkinson RR, Sharkey KJ. Deterministic epidemic models overestimate the basic reproduction number of observed outbreaks. Infect Dis Model 2024; 9:680-688. [PMID: 38638338 PMCID: PMC11024615 DOI: 10.1016/j.idm.2024.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 04/20/2024] Open
Abstract
The basic reproduction number, R0, is a well-known quantifier of epidemic spread. However, a class of existing methods for estimating R0 from incidence data early in the epidemic can lead to an over-estimation of this quantity. In particular, when fitting deterministic models to estimate the rate of spread, we do not account for the stochastic nature of epidemics and that, given the same system, some outbreaks may lead to epidemics and some may not. Typically, an observed epidemic that we wish to control is a major outbreak. This amounts to implicit selection for major outbreaks which leads to the over-estimation problem. We formally characterised the split between major and minor outbreaks by using Otsu's method which provides us with a working definition. We show that by conditioning a 'deterministic' model on major outbreaks, we can more reliably estimate the basic reproduction number from an observed epidemic trajectory.
Collapse
Affiliation(s)
- Wajid Ali
- Department of Mathematical Sciences, University of Liverpool, Peach Street, Liverpool, L69 7ZX, England, United Kingdom
| | - Christopher E. Overton
- Department of Mathematical Sciences, University of Liverpool, Peach Street, Liverpool, L69 7ZX, England, United Kingdom
| | - Robert R. Wilkinson
- Department of Applied Mathematics, Liverpool John Moores University, Byrom Street, Liverpool, L3 5UX, England, United Kingdom
| | - Kieran J. Sharkey
- Department of Mathematical Sciences, University of Liverpool, Peach Street, Liverpool, L69 7ZX, England, United Kingdom
| |
Collapse
|
2
|
Conesa D, López de Rioja V, Gullón T, Tauste Campo A, Prats C, Alvarez-Lacalle E, Echebarria B. A mixture of mobility and meteorological data provides a high correlation with COVID-19 growth in an infection-naive population: a study for Spanish provinces. Front Public Health 2024; 12:1288531. [PMID: 38528860 PMCID: PMC10962055 DOI: 10.3389/fpubh.2024.1288531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 02/16/2024] [Indexed: 03/27/2024] Open
Abstract
Introduction We use Spanish data from August 2020 to March 2021 as a natural experiment to analyze how a standardized measure of COVID-19 growth correlates with asymmetric meteorological and mobility situations in 48 Spanish provinces. The period of time is selected prior to vaccination so that the level of susceptibility was high, and during geographically asymmetric implementation of non-pharmacological interventions. Methods We develop reliable aggregated mobility data from different public sources and also compute the average meteorological time series of temperature, dew point, and UV radiance in each Spanish province from satellite data. We perform a dimensionality reduction of the data using principal component analysis and investigate univariate and multivariate correlations of mobility and meteorological data with COVID-19 growth. Results We find significant, but generally weak, univariate correlations for weekday aggregated mobility in some, but not all, provinces. On the other hand, principal component analysis shows that the different mobility time series can be properly reduced to three time series. A multivariate time-lagged canonical correlation analysis of the COVID-19 growth rate with these three time series reveals a highly significant correlation, with a median R-squared of 0.65. The univariate correlation between meteorological data and COVID-19 growth is generally not significant, but adding its two main principal components to the mobility multivariate analysis increases correlations significantly, reaching correlation coefficients between 0.6 and 0.98 in all provinces with a median R-squared of 0.85. This result is robust to different approaches in the reduction of dimensionality of the data series. Discussion Our results suggest an important effect of mobility on COVID-19 cases growth rate. This effect is generally not observed for meteorological variables, although in some Spanish provinces it can become relevant. The correlation between mobility and growth rate is maximal at a time delay of 2-3 weeks, which agrees well with the expected 5?10 day delays between infection, development of symptoms, and the detection/report of the case.
Collapse
Affiliation(s)
- David Conesa
- Department of Physics, Universitat Politécnica de Catalunya, Barcelona, Spain
| | | | - Tania Gullón
- Spanish Ministry of Transport, Mobility and Urban Agenda (MITMA), Madrid, Spain
| | - Adriá Tauste Campo
- Department of Physics, Universitat Politécnica de Catalunya, Barcelona, Spain
| | - Clara Prats
- Department of Physics, Universitat Politécnica de Catalunya, Barcelona, Spain
| | | | - Blas Echebarria
- Department of Physics, Universitat Politécnica de Catalunya, Barcelona, Spain
| |
Collapse
|
3
|
Aldossari HM, Salam AA. COVID-19 infections, recoveries, and mortality: an ANOVA model of locations and administrative areas in Saudi Arabia. Front Public Health 2024; 12:1281289. [PMID: 38299074 PMCID: PMC10829572 DOI: 10.3389/fpubh.2024.1281289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/03/2024] [Indexed: 02/02/2024] Open
Abstract
Background Saudi Arabia has 13 administrative areas, all of which have been seriously affected by the COVID-19 epidemic regardless of their features. Being the largest and a prominent Arab country, epidemic intensity and dynamics have importance, especially in the era of Vision 2030 where infrastructure development and growth to enhance quality of life has of prime focus. Aims This analysis aims to trace the differentials in COVID-19 infections, recoveries, and deaths across the country depending upon various demographic and developmental dimensions and interactions. Data and methods This analysis used Saudi Arabia Ministry of Health data from March 15th, 2020 to August 31st, 2022, by classifying administrative areas and locations to build a generalized linear model (3 × 3): three types of administrative areas (major, middle-sized, and others) and localities (major, medium-sized, and others). Apart from two-way ANOVA, an one-way ANOVA also carried out in addition to calculating mean values of infections, recoveries, and deaths. Results A total of 205 localities were affected with varying severity, which are based on local demographics. Both the administrative areas and localities had a significant number of cases of infections, recoveries, and mortality, which are influenced by relationships and interactions, leading to differential mean values and proportional distributions across various types of administrative areas and localities. Conclusion There is dynamism that major administrative areas have lesser threats from the epidemics whereas medium-sized ones have serious threats. Moreover, an interaction of administrative areas and localities explains the dynamics of epidemic spread under varying levels of infrastructure preparedness. Thus, this study presents lessons learned to inform policies, programs, and development plans, especially for regional, urban, and infrastructure areas, considering grassroots level issues and diversity.
Collapse
Affiliation(s)
- Hamad Mansur Aldossari
- Geography and Geographical Information Systems Department, College of Social Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
| | | |
Collapse
|
4
|
Jia H, Zheng M, Wang P, Li T, Zheng X. Big data-driven spatio-temporal heterogeneity analysis of Beijing's catering service industry during the COVID-19 pandemic. Sci Rep 2024; 14:721. [PMID: 38184685 PMCID: PMC10771444 DOI: 10.1038/s41598-024-51251-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/02/2024] [Indexed: 01/08/2024] Open
Abstract
The Catering Service Industry (CSI) experienced profound impacts due to the COVID-19 pandemic. However, the long-term and multi-timepoint analysis using big data remained limited, influencing governmental decision-making. We applied Kernel Density Estimation, Shannon Diversity Index, and the Geographic detector to explore the spatial heterogeneity and determinants of the CSI in Beijing during the pandemic, with monthly granularity. The temporal-spatial dynamics of the CSI presented a "W"-shaped trend from 2018 to 2023, with pivotal shifts aligning with key pandemic stages. Spatial characteristics exhibited heterogeneity, with greater stability in the city center and more pronounced shifts in peripheral urban zones. Districts facing intricate outbreaks showed lower catering income, and Chinese eateries exhibited heightened resilience compared to others. The CSI displayed strong interconnections with living service sectors. Development in each district was influenced by economic level, population distribution, service facilities convenience, and the risk of the COVID-19 pandemic. Dominant factors included total retail sales of consumer goods, permanent population, average Baidu Heat Index, density of transportation and catering service facilities, infection cases and the consecutive days with confirmed cases existing. Consequently, we suggested seizing post-pandemic recovery as an avenue to unlock the CSI's substantial potential, ushering a fresh phase of growth.
Collapse
Affiliation(s)
- Haichao Jia
- School of Information Engineering, China University of Geosciences, Beijing, 100083, China
| | - Minrui Zheng
- School of Public Administration and Policy, Renmin University of China, Beijing, 100872, China.
- Digital Government and National Governance Lab, Renmin University of China, Beijing, 100872, China.
| | - Peipei Wang
- School of Information Engineering, China University of Geosciences, Beijing, 100083, China
| | - Tianle Li
- School of Information Engineering, China University of Geosciences, Beijing, 100083, China
| | - Xinqi Zheng
- School of Information Engineering, China University of Geosciences, Beijing, 100083, China
- Technology Innovation Center for Territory Spatial Big-Data, MNR of China, Beijing, 100036, China
- Beijing Fangshan Observation and Research Station of Comprehensive Exploration Technology, Ministry of Natural Resources of People's Republic of China, Beijing, 102400, China
| |
Collapse
|
5
|
Sabbatini CE, Pullano G, Di Domenico L, Rubrichi S, Bansal S, Colizza V. The impact of spatial connectivity on NPIs effectiveness. BMC Infect Dis 2024; 24:21. [PMID: 38166649 PMCID: PMC10763474 DOI: 10.1186/s12879-023-08900-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND France implemented a combination of non-pharmaceutical interventions (NPIs) to manage the COVID-19 pandemic between September 2020 and June 2021. These included a lockdown in the fall 2020 - the second since the start of the pandemic - to counteract the second wave, followed by a long period of nighttime curfew, and by a third lockdown in the spring 2021 against the Alpha wave. Interventions have so far been evaluated in isolation, neglecting the spatial connectivity between regions through mobility that may impact NPI effectiveness. METHODS Focusing on September 2020-June 2021, we developed a regionally-based epidemic metapopulation model informed by observed mobility fluxes from daily mobile phone data and fitted the model to regional hospital admissions. The model integrated data on vaccination and variants spread. Scenarios were designed to assess the impact of the Alpha variant, characterized by increased transmissibility and risk of hospitalization, of the vaccination campaign and alternative policy decisions. RESULTS The spatial model better captured the heterogeneity observed in the regional dynamics, compared to models neglecting inter-regional mobility. The third lockdown was similarly effective to the second lockdown after discounting for immunity, Alpha, and seasonality (51% vs 52% median regional reduction in the reproductive number R0, respectively). The 6pm nighttime curfew with bars and restaurants closed, implemented in January 2021, substantially reduced COVID-19 transmission. It initially led to 49% median regional reduction of R0, decreasing to 43% reduction by March 2021. In absence of vaccination, implemented interventions would have been insufficient against the Alpha wave. Counterfactual scenarios proposing a sequence of lockdowns in a stop-and-go fashion would have reduced hospitalizations and restriction days for low enough thresholds triggering and lifting restrictions. CONCLUSIONS Spatial connectivity induced by mobility impacted the effectiveness of interventions especially in regions with higher mobility rates. Early evening curfew with gastronomy sector closed allowed authorities to delay the third wave. Stop-and-go lockdowns could have substantially lowered both healthcare and societal burdens if implemented early enough, compared to the observed application of lockdown-curfew-lockdown, but likely at the expense of several labor sectors. These findings contribute to characterize the effectiveness of implemented strategies and improve pandemic preparedness.
Collapse
Affiliation(s)
- Chiara E Sabbatini
- Sorbonne Université, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Giulia Pullano
- Department of Biology, Georgetown University, Washington, DC, USA
| | - Laura Di Domenico
- Sorbonne Université, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Stefania Rubrichi
- Orange Labs, Sociology and Economics of Networks and Services (SENSE), Chatillon, France
| | - Shweta Bansal
- Department of Biology, Georgetown University, Washington, DC, USA
| | - Vittoria Colizza
- Sorbonne Université, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.
| |
Collapse
|
6
|
Han J, Yin J, Wu X, Wang D, Li C. Environment and COVID-19 incidence: A critical review. J Environ Sci (China) 2023; 124:933-951. [PMID: 36182196 PMCID: PMC8858699 DOI: 10.1016/j.jes.2022.02.016] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 01/27/2022] [Accepted: 02/10/2022] [Indexed: 05/19/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented worldwide health crisis. Many previous research studies have found and investigated its links with one or some natural or human environmental factors. However, a review on the relationship between COVID-19 incidence and both the natural and human environment is still lacking. This review summarizes the inter-correlation between COVID-19 incidence and environmental factors. Based on keyword searching, we reviewed 100 relevant peer-reviewed articles and other research literature published since January 2020. This review is focused on three main findings. One, we found that individual environmental factors have impacts on COVID-19 incidence, but with spatial heterogeneity and uncertainty. Two, environmental factors exert interactive effects on COVID-19 incidence. In particular, the interactions of natural factors can affect COVID-19 transmission in micro- and macro- ways by impacting SARS-CoV-2 survival, as well as human mobility and behaviors. Three, the impact of COVID-19 incidence on the environment lies in the fact that COVID-19-induced lockdowns caused air quality improvement, wildlife shifts and socio-economic depression. The additional value of this review is that we recommend future research perspectives and adaptation strategies regarding the interactions of the environment and COVID-19. Future research should be extended to cover both the effects of the environment on the COVID-19 pandemic and COVID-19-induced impacts on the environment. Future adaptation strategies should focus on sustainable environmental and public policy responses.
Collapse
Affiliation(s)
- Jiatong Han
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Jie Yin
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Xiaoxu Wu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
| | - Danyang Wang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Chenlu Li
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
7
|
Hassan MA, Mehmood T, Lodhi E, Bilal M, Dar AA, Liu J. Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13540. [PMID: 36294120 PMCID: PMC9603700 DOI: 10.3390/ijerph192013540] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/10/2022] [Accepted: 10/15/2022] [Indexed: 06/16/2023]
Abstract
Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.
Collapse
Affiliation(s)
- Muhammad Azher Hassan
- Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
| | - Tariq Mehmood
- College of Ecology and Environment, Hainan University, Haikou 570228, China
- Department of Environmental Engineering, Helmholtz Centre for Environmental Research—UFZ, D-04318 Leipzig, Germany
| | - Ehtisham Lodhi
- The SKL for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Muhammad Bilal
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
| | - Afzal Ahmed Dar
- School of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi’an 710000, China
| | - Junjie Liu
- Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
| |
Collapse
|
8
|
Truszkowska A, Fayed M, Wei S, Zino L, Butail S, Caroppo E, Jiang ZP, Rizzo A, Porfiri M. Urban Determinants of COVID-19 Spread: a Comparative Study across Three Cities in New York State. J Urban Health 2022; 99:909-921. [PMID: 35668138 PMCID: PMC9170119 DOI: 10.1007/s11524-022-00623-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/17/2022] [Indexed: 12/24/2022]
Abstract
The ongoing pandemic is laying bare dramatic differences in the spread of COVID-19 across seemingly similar urban environments. Identifying the urban determinants that underlie these differences is an open research question, which can contribute to more epidemiologically resilient cities, optimized testing and detection strategies, and effective immunization efforts. Here, we perform a computational analysis of COVID-19 spread in three cities of similar size in New York State (Colonie, New Rochelle, and Utica) aiming to isolate urban determinants of infections and deaths. We develop detailed digital representations of the cities and simulate COVID-19 spread using a complex agent-based model, taking into account differences in spatial layout, mobility, demographics, and occupational structure of the population. By critically comparing pandemic outcomes across the three cities under equivalent initial conditions, we provide compelling evidence in favor of the central role of hospitals. Specifically, with highly efficacious testing and detection, the number and capacity of hospitals, as well as the extent of vaccination of hospital employees are key determinants of COVID-19 spread. The modulating role of these determinants is reduced at lower efficacy of testing and detection, so that the pandemic outcome becomes equivalent across the three cities.
Collapse
Affiliation(s)
- Agnieszka Truszkowska
- Center for Urban Science and Progress, Tandon School of Engineering, New York University, Brooklyn, NY, USA
- Department of Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA
| | - Maya Fayed
- New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Sihan Wei
- Center for Urban Science and Progress, Tandon School of Engineering, New York University, Brooklyn, NY, USA
| | - Lorenzo Zino
- Faculty of Science and Engineering, University of Groningen, Groningen, The Netherlands
| | - Sachit Butail
- Department of Mechanical Engineering, Northern Illinois University, DeKalb, IL, USA
| | - Emanuele Caroppo
- Department of Mental Health, Local Health Unit ROMA 2, Rome, Italy
- University Research Center He.R.A., Università Cattolica del Sacro Cuore, Rome, Italy
| | - Zhong-Ping Jiang
- Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA
| | - Alessandro Rizzo
- Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
- Institute for Invention, Innovation, and Entrepreneurship, Tandon School of Engineering, New York University, Brooklyn, NY, USA
| | - Maurizio Porfiri
- Center for Urban Science and Progress, Tandon School of Engineering, New York University, Brooklyn, NY, USA.
- Department of Mechanical and Aerospace Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA.
- Department of Biomedical Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA.
| |
Collapse
|
9
|
Scabbia G, Sanfilippo A, Mazzoni A, Bachour D, Perez-Astudillo D, Bermudez V, Wey E, Marchand-Lasserre M, Saboret L. Does climate help modeling COVID-19 risk and to what extent? PLoS One 2022; 17:e0273078. [PMID: 36070304 PMCID: PMC9451080 DOI: 10.1371/journal.pone.0273078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 08/01/2022] [Indexed: 11/25/2022] Open
Abstract
A growing number of studies suggest that climate may impact the spread of COVID-19. This hypothesis is supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data. However, the extent to which climate may affect COVID-19 transmission rates and help modeling COVID-19 risk is still not well understood. This study demonstrates that such an understanding is attainable through the development of regression models that verify how climate contributes to modeling COVID-19 transmission, and the use of feature importance techniques that assess the relative weight of meteorological variables compared to epidemiological, socioeconomic, environmental, and global health factors. The ensuing results show that meteorological factors play a key role in regression models of COVID-19 risk, with ultraviolet radiation (UV) as the main driver. These results are corroborated by statistical correlation analyses and a panel data fixed-effect model confirming that UV radiation coefficients are significantly negatively correlated with COVID-19 transmission rates.
Collapse
Affiliation(s)
- Giovanni Scabbia
- Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar
| | - Antonio Sanfilippo
- Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar
- * E-mail:
| | - Annamaria Mazzoni
- Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar
| | - Dunia Bachour
- Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar
| | - Daniel Perez-Astudillo
- Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar
| | - Veronica Bermudez
- Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar
| | | | | | | |
Collapse
|
10
|
Cao Y, Whittington JD, Kausrud K, Li R, Stenseth NC. The Relative Contribution of Climatic, Demographic Factors, Disease Control Measures and Spatiotemporal Heterogeneity to Variation of Global COVID-19 Transmission. GEOHEALTH 2022; 6:e2022GH000589. [PMID: 35946036 PMCID: PMC9349723 DOI: 10.1029/2022gh000589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 06/24/2022] [Accepted: 06/30/2022] [Indexed: 06/15/2023]
Abstract
Despite a substantial number of COVID-19 related research papers published, it remains unclear as to which factors are associated with the observed variation in global transmission and what are their relative levels of importance. This study applies a rigorous statistical framework to provide robust estimations of the factor effects for a global and integrated perspective on this issue. We developed a mixed effect model exploring the relative importance of potential factors driving COVID-19 transmission while incorporating spatial and temporal heterogeneity of spread. We use an integrated data set for 87 countries across six continents for model specification and fitting. The best model accounts for 70.4% of the variance in the data analyzed: 10 fixed effect factors explain 20.5% of the variance, random temporal and spatial effects account for 50% of the variance. The fixed effect factors are classified into climatic, demographic and disease control groups. The explained variance in global transmission by the three groups are 0.6%, 1.1%, and 4.4% respectively. The high proportion of variance accounted for by random effects indicated striking differences in temporal transmission trajectories and effects of population mobility among the countries. In particular, the country-specific mobility-transmission relationship turns out to be the most important factor in explaining the observed global variation of transmission in the early phase of COVID-19 pandemic.
Collapse
Affiliation(s)
- Yihan Cao
- Centre for Ecological and Evolutionary Synthesis (CEES)Department of BiosciencesUniversity of OsloOsloNorway
| | - Jason D. Whittington
- Centre for Ecological and Evolutionary Synthesis (CEES)Department of BiosciencesUniversity of OsloOsloNorway
| | | | - Ruiyun Li
- Centre for Ecological and Evolutionary Synthesis (CEES)Department of BiosciencesUniversity of OsloOsloNorway
| | - Nils Chr. Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES)Department of BiosciencesUniversity of OsloOsloNorway
| |
Collapse
|
11
|
Associations between COVID-19 Pandemic, Lockdown Measures and Human Mobility: Longitudinal Evidence from 86 Countries. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19127317. [PMID: 35742567 PMCID: PMC9223807 DOI: 10.3390/ijerph19127317] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/12/2022] [Accepted: 06/13/2022] [Indexed: 12/18/2022]
Abstract
Recognizing an urgent need to understand the dynamics of the pandemic’s severity, this longitudinal study is conducted to explore the evolution of complex relationships between the COVID-19 pandemic, lockdown measures, and social distancing patterns in a diverse set of 86 countries. Collecting data from multiple sources, a structural equation modeling (SEM) technique is applied to understand the interdependencies between independent variables, mediators, and dependent variables. Results show that lockdown and confinement measures are very effective to reduce human mobility at retail and recreation facilities, transit stations, and workplaces and encourage people to stay home and thereby control COVID-19 transmission at critical times. The study also found that national contexts rooted in socioeconomic and institutional factors influence social distancing patterns and severity of the pandemic, particularly with regard to the vulnerability of people, treatment costs, level of globalization, employment distribution, and degree of independence in society. Additionally, this study portrayed a mutual relationship between the COVID-19 pandemic and human mobility. A higher number of COVID-19 confirmed cases and deaths reduces human mobility and the countries with reduced personal mobility have experienced a deepening of the severity of the pandemic. However, the effect of mobility on pandemic severity is stronger than the effect of pandemic situations on mobility. Overall, the study displays considerable temporal changes in the relationships between independent variables, mediators, and dependent variables considering pandemic situations and lockdown regimes, which provides a critical knowledge base for future handling of pandemics. It has also accommodated some policy guidelines for the authority to control the transmission of COVID-19.
Collapse
|
12
|
Mariam SH. The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Pandemic: Are Africa's Prevalence and Mortality Rates Relatively Low? Adv Virol 2022; 2022:3387784. [PMID: 35256885 PMCID: PMC8898136 DOI: 10.1155/2022/3387784] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/14/2022] [Accepted: 01/28/2022] [Indexed: 12/13/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of coronavirus disease 19 (COVID-19), has been rapidly spreading since December 2019, and within a few months, it turned out to be a global pandemic. The disease affects primarily the lungs, but its pathogenesis spreads to other organs as well. However, its mortality rates vary, and in the majority of infected people, there are no serious consequences. Many factors including advanced age, preexisting health conditions, and genetic predispositions are believed to exacerbate outcomes of COVID-19. The virus contains several structural proteins including the spike (S) protein with subunits for binding, fusion, and internalization into host cells following interaction with host cell receptors and proteases (ACE2 and TMPRSS2, respectively) to cause the subsequent pathology. Although the pandemic has spread into all countries, most of Africa is thought of as having relatively less prevalence and mortality. Several hypotheses have been forwarded as reasons for this and include warmer weather conditions, vaccination with BCG (i.e., trained immunity), and previous malaria infection. From genetics or metabolic points of view, it has been proposed that most African populations could be protected to some degree because they lack some genetic susceptibility risk factors or have low-level expression of allelic variants, such as ACE2 and TMPRSS2 that are thought to be involved in increased infection risk or disease severity. The frequency of occurrence of α-1 antitrypsin (an inhibitor of a tissue-degrading protease, thereby protecting target host tissues including the lung) deficiency is also reported to be low in most African populations. More recently, infections in Africa appear to be on the rise. In general, there are few studies on the epidemiology and pathogenesis of the disease in African contexts, and the overall costs and human life losses due to the pandemic in Africa will be determined by all factors and conditions interacting in complex ways.
Collapse
Affiliation(s)
- Solomon H. Mariam
- Infectious Diseases Program, Aklilu Lemma Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
| |
Collapse
|
13
|
Potential Contribution of Climate Conditions on COVID-19 Pandemic Transmission over West and North African Countries. ATMOSPHERE 2021. [DOI: 10.3390/atmos13010034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a very contagious disease that has killed many people worldwide. According to data from the World Health Organization (WHO), the spread of the disease appears to be slower in Africa. Although several studies have been published on the relationship between meteorological parameters and COVID-19 transmission, the effects of climate conditions on COVID-19 remain largely unexplored and without consensus. However, the transmission of COVID-19 and sensitivity to climate conditions are also not fully understood in Africa. Here, using available epidemiological data over 275 days (i.e., from 1 March to 30 November 2020) taken from the European Center for Disease Prevention and Control of the European Union database and daily data of surface air temperature specific humidity and water vapor from the National Center for Environmental Prediction (NCEP), this paper investigates the potential contribution of climate conditions on COVID-19 transmission over 16 selected countries throughout three climatic regions of Africa (i.e., Sahel, Maghreb, and Gulf of Guinea). The results highlight statistically significant inverse correlations between COVID-19 cases and temperature over the Maghreb and the Gulf of Guinea regions. In contrast, positive correlations are found over the Sahel area, especially in the central part, including Niger and Mali. Correlations with specific humidity and water vapor parameters display significant and positive values over the Sahelian and the Gulf of Guinea countries and negative values over the Maghreb countries. Then, the COVID-19 pandemic transmission is influenced differently across the three climatic regions: (i) cold and dry environmental conditions over the Maghreb; (ii) warm and humid conditions over the Sahel; and (iii) cold and humid conditions over the Gulf of Guinea. In addition, for all three climatic regions, even though the climate impact has been found to be significant, its effect appears to display a secondary role based on the explanatory power variance compared to non-climatic factors assumed to be dominated by socio-economic factors and early strong public health measures.
Collapse
|
14
|
Di Domenico L, Sabbatini CE, Boëlle PY, Poletto C, Crépey P, Paireau J, Cauchemez S, Beck F, Noel H, Lévy-Bruhl D, Colizza V. Adherence and sustainability of interventions informing optimal control against the COVID-19 pandemic. COMMUNICATIONS MEDICINE 2021; 1:57. [PMID: 35602184 PMCID: PMC9053235 DOI: 10.1038/s43856-021-00057-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 11/10/2021] [Indexed: 11/08/2022] Open
Abstract
Background After one year of stop-and-go COVID-19 mitigation, in the spring of 2021 European countries still experienced sustained viral circulation due to the Alpha variant. As the prospect of entering a new pandemic phase through vaccination was drawing closer, a key challenge remained on how to balance the efficacy of long-lasting interventions and their impact on the quality of life. Methods Focusing on the third wave in France during spring 2021, we simulate intervention scenarios of varying intensity and duration, with potential waning of adherence over time, based on past mobility data and modeling estimates. We identify optimal strategies by balancing efficacy of interventions with a data-driven "distress" index, integrating intensity and duration of social distancing. Results We show that moderate interventions would require a much longer time to achieve the same result as high intensity lockdowns, with the additional risk of deteriorating control as adherence wanes. Shorter strict lockdowns are largely more effective than longer moderate lockdowns, for similar intermediate distress and infringement on individual freedom. Conclusions Our study shows that favoring milder interventions over more stringent short approaches on the basis of perceived acceptability could be detrimental in the long term, especially with waning adherence.
Collapse
Affiliation(s)
- Laura Di Domenico
- INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Chiara E. Sabbatini
- INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Pierre-Yves Boëlle
- INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Chiara Poletto
- INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Pascal Crépey
- Univ Rennes, EHESP, REPERES « Recherche en Pharmaco-Epidémiologie et Recours aux Soins »—EA 7449, 35043 Rennes, France
| | - Juliette Paireau
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
- Santé Publique France, French National Public Health Agency, Saint-Maurice, France
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | - François Beck
- Santé Publique France, French National Public Health Agency, Saint-Maurice, France
| | - Harold Noel
- Santé Publique France, French National Public Health Agency, Saint-Maurice, France
| | - Daniel Lévy-Bruhl
- Santé Publique France, French National Public Health Agency, Saint-Maurice, France
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
- Tokyo Tech World Research Hub Initiative, Institute of Innovative Research, Tokyo Institute of Technology, Tokyo, Japan
| |
Collapse
|
15
|
Fronteira I, Sidat M, Magalhães JP, de Barros FPC, Delgado AP, Correia T, Daniel-Ribeiro CT, Ferrinho P. The SARS-CoV-2 pandemic: A syndemic perspective. One Health 2021; 12:100228. [PMID: 33614885 PMCID: PMC7887445 DOI: 10.1016/j.onehlt.2021.100228] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 02/10/2021] [Accepted: 02/11/2021] [Indexed: 01/07/2023] Open
Abstract
The SARS-CoV-2 pandemic has affected communities, populations, and countries throughout the world. As the SARS-CoV-2 pandemic developed, the extent to which the disease interacted with already existing endemic, non-communicable and infectious diseases became evident, hence deeply influencing health outcomes. Additionally, a synergistic effect has been demonstrated also with socio-economic, cultural, and contextual determinants of health which seem to contribute to poorer health and accumulating social disadvantages. In this essay, using as a starting point the syndemic theory that translates the cumulative and intertwined factors between different epidemics, we argue that the SARS-CoV-2 is a one health issue of a syndemic nature and that the failure to acknowledge this contributes to weakened policy-making processes and public health responses and ineffective health policies and programs.
Collapse
Affiliation(s)
- Inês Fronteira
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Portugal,Corresponding author.
| | - Mohsin Sidat
- Community Health Department, Faculty of Medicine, University Eduardo Mondlane, Mozambique
| | - João Paulo Magalhães
- Public Health Unit, Group of Primary Care Centers of Porto Oriental, North Health Regional Administration, Ministry of Health, Portugal
| | | | - António Pedro Delgado
- University of Cabo Verde, Cabo Verde, Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Portugal
| | - Tiago Correia
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Portugal
| | - Cláudio Tadeu Daniel-Ribeiro
- Laboratório de Pesquisa em Malária, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro and Centro de Pesquisa Diagnóstico e Treinamento em Malária, Fiocruz e Secretaria de Vigilância em Saúde, Brazil
| | - Paulo Ferrinho
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Portugal
| |
Collapse
|