1
|
Abrams S, Wambua J, Santermans E, Willem L, Kuylen E, Coletti P, Libin P, Faes C, Petrof O, Herzog SA, Beutels P, Hens N. Modelling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories. Epidemics 2021; 35:100449. [PMID: 33799289 PMCID: PMC7986325 DOI: 10.1016/j.epidem.2021.100449] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 02/09/2021] [Accepted: 03/04/2021] [Indexed: 02/08/2023] Open
Abstract
Following the onset of the ongoing COVID-19 pandemic throughout the world, a large fraction of the global population is or has been under strict measures of physical distancing and quarantine, with many countries being in partial or full lockdown. These measures are imposed in order to reduce the spread of the disease and to lift the pressure on healthcare systems. Estimating the impact of such interventions as well as monitoring the gradual relaxing of these stringent measures is quintessential to understand how resurgence of the COVID-19 epidemic can be controlled for in the future. In this paper we use a stochastic age-structured discrete time compartmental model to describe the transmission of COVID-19 in Belgium. Our model explicitly accounts for age-structure by integrating data on social contacts to (i) assess the impact of the lockdown as implemented on March 13, 2020 on the number of new hospitalizations in Belgium; (ii) conduct a scenario analysis estimating the impact of possible exit strategies on potential future COVID-19 waves. More specifically, the aforementioned model is fitted to hospital admission data, data on the daily number of COVID-19 deaths and serial serological survey data informing the (sero)prevalence of the disease in the population while relying on a Bayesian MCMC approach. Our age-structured stochastic model describes the observed outbreak data well, both in terms of hospitalizations as well as COVID-19 related deaths in the Belgian population. Despite an extensive exploration of various projections for the future course of the epidemic, based on the impact of adherence to measures of physical distancing and a potential increase in contacts as a result of the relaxation of the stringent lockdown measures, a lot of uncertainty remains about the evolution of the epidemic in the next months.
Collapse
Affiliation(s)
- Steven Abrams
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium; Global Health Institute, Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium.
| | - James Wambua
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium
| | - Eva Santermans
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium
| | - Lander Willem
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Elise Kuylen
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Pietro Coletti
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium
| | - Pieter Libin
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium; Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium; Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, University of Leuven, Leuven, Belgium
| | - Christel Faes
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium
| | - Oana Petrof
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium
| | - Sereina A Herzog
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Niel Hens
- Data Science Institute, Interuniversity Institute of Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium; Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| |
Collapse
|
2
|
Coletti P, Libin P, Petrof O, Willem L, Abrams S, Herzog SA, Faes C, Kuylen E, Wambua J, Beutels P, Hens N. A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies. BMC Infect Dis 2021; 21:503. [PMID: 34053446 PMCID: PMC8164894 DOI: 10.1186/s12879-021-06092-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 04/20/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND In response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks. METHODS We analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown. RESULTS Our model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period. CONCLUSIONS Contacts during leisure activities are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment of social contacts in the population is therefore crucial to adjust to evolving behavioral changes that can affect epidemic diffusion.
Collapse
Affiliation(s)
- Pietro Coletti
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium.
| | - Pieter Libin
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
- Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium
- Rega Institute for Medical Research, Katholieke Universiteit Leuven, Herestraat 49, Leuven, 3000, Belgium
| | - Oana Petrof
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
| | - Lander Willem
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, 2610, Belgium
| | - Steven Abrams
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
- Global Health Institute, Family Medicine and Population Health, University of Antwerp, Wilrijk, Belgium
| | - Sereina A Herzog
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, 2610, Belgium
- Institute for Medical Informatics, Statistics and Documentation, Auenbruggerplatz 2, Graz, 8036, Austria
| | - Christel Faes
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
| | - Elise Kuylen
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, 2610, Belgium
| | - James Wambua
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, 2610, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia
| | - Niel Hens
- Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek, 3590, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Universiteitsplein 1, Wilrijk, 2610, Belgium
| |
Collapse
|
3
|
Willem L, Abrams S, Libin PJK, Coletti P, Kuylen E, Petrof O, Møgelmose S, Wambua J, Herzog SA, Faes C, Beutels P, Hens N. The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19. Nat Commun 2021. [PMID: 33750778 DOI: 10.1038/s41467-021-21747] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023] Open
Abstract
The COVID-19 pandemic caused many governments to impose policies restricting social interactions. A controlled and persistent release of lockdown measures covers many potential strategies and is subject to extensive scenario analyses. Here, we use an individual-based model (STRIDE) to simulate interactions between 11 million inhabitants of Belgium at different levels including extended household settings, i.e., "household bubbles". The burden of COVID-19 is impacted by both the intensity and frequency of physical contacts, and therefore, household bubbles have the potential to reduce hospital admissions by 90%. In addition, we find that it is crucial to complete contact tracing 4 days after symptom onset. Assumptions on the susceptibility of children affect the impact of school reopening, though we find that business and leisure-related social mixing patterns have more impact on COVID-19 associated disease burden. An optimal deployment of the mitigation policies under study require timely compliance to physical distancing, testing and self-isolation.
Collapse
Affiliation(s)
- Lander Willem
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium.
| | - Steven Abrams
- Data Science Institute, UHasselt, Hasselt, Belgium
- Global Health Institute, University of Antwerp, Antwerp, Belgium
| | - Pieter J K Libin
- Data Science Institute, UHasselt, Hasselt, Belgium
- Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium
- Rega Institute for Medical Research, Clinical and Epidemiological Virology, University of Leuven, Leuven, Belgium
| | | | - Elise Kuylen
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, UHasselt, Hasselt, Belgium
| | - Oana Petrof
- Data Science Institute, UHasselt, Hasselt, Belgium
| | - Signe Møgelmose
- Data Science Institute, UHasselt, Hasselt, Belgium
- Centre for Population, Family and Health, University of Antwerp, Antwerp, Belgium
| | - James Wambua
- Data Science Institute, UHasselt, Hasselt, Belgium
| | - Sereina A Herzog
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
| | | | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, NSW, Australia
| | - Niel Hens
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, UHasselt, Hasselt, Belgium
| |
Collapse
|
4
|
Willem L, Abrams S, Libin PJK, Coletti P, Kuylen E, Petrof O, Møgelmose S, Wambua J, Herzog SA, Faes C, Beutels P, Hens N. The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19. Nat Commun 2021; 12:1524. [PMID: 33750778 PMCID: PMC7943552 DOI: 10.1038/s41467-021-21747-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 02/09/2021] [Indexed: 01/20/2023] Open
Abstract
The COVID-19 pandemic caused many governments to impose policies restricting social interactions. A controlled and persistent release of lockdown measures covers many potential strategies and is subject to extensive scenario analyses. Here, we use an individual-based model (STRIDE) to simulate interactions between 11 million inhabitants of Belgium at different levels including extended household settings, i.e., "household bubbles". The burden of COVID-19 is impacted by both the intensity and frequency of physical contacts, and therefore, household bubbles have the potential to reduce hospital admissions by 90%. In addition, we find that it is crucial to complete contact tracing 4 days after symptom onset. Assumptions on the susceptibility of children affect the impact of school reopening, though we find that business and leisure-related social mixing patterns have more impact on COVID-19 associated disease burden. An optimal deployment of the mitigation policies under study require timely compliance to physical distancing, testing and self-isolation.
Collapse
Affiliation(s)
- Lander Willem
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium.
| | - Steven Abrams
- Data Science Institute, UHasselt, Hasselt, Belgium
- Global Health Institute, University of Antwerp, Antwerp, Belgium
| | - Pieter J K Libin
- Data Science Institute, UHasselt, Hasselt, Belgium
- Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium
- Rega Institute for Medical Research, Clinical and Epidemiological Virology, University of Leuven, Leuven, Belgium
| | | | - Elise Kuylen
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, UHasselt, Hasselt, Belgium
| | - Oana Petrof
- Data Science Institute, UHasselt, Hasselt, Belgium
| | - Signe Møgelmose
- Data Science Institute, UHasselt, Hasselt, Belgium
- Centre for Population, Family and Health, University of Antwerp, Antwerp, Belgium
| | - James Wambua
- Data Science Institute, UHasselt, Hasselt, Belgium
| | - Sereina A Herzog
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
| | | | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, NSW, Australia
| | - Niel Hens
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, UHasselt, Hasselt, Belgium
| |
Collapse
|
5
|
Zhang J, Klepac P, Read JM, Rosello A, Wang X, Lai S, Li M, Song Y, Wei Q, Jiang H, Yang J, Lynn H, Flasche S, Jit M, Yu H. Patterns of human social contact and contact with animals in Shanghai, China. Sci Rep 2019; 9:15141. [PMID: 31641189 PMCID: PMC6805924 DOI: 10.1038/s41598-019-51609-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Accepted: 09/29/2019] [Indexed: 12/17/2022] Open
Abstract
East Asia is as a principal hotspot for emerging zoonotic infections. Understanding the likely pathways for their emergence and spread requires knowledge on human-human and human-animal contacts, but such studies are rare. We used self-completed and interviewer-completed contact diaries to quantify patterns of these contacts for 965 individuals in 2017/2018 in a high-income densely-populated area of China, Shanghai City. Interviewer-completed diaries recorded more social contacts (19.3 vs. 18.0) and longer social contact duration (35.0 vs. 29.1 hours) than self-reporting. Strong age-assortativity was observed in all age groups especially among young participants (aged 7-20) and middle aged participants (25-55 years). 17.7% of participants reported touching animals (15.3% (pets), 0.0% (poultry) and 0.1% (livestock)). Human-human contact was very frequent but contact with animals (especially poultry) was rare although associated with frequent human-human contact. Hence, this densely populated area is more likely to act as an accelerator for human-human spread but less likely to be at the source of a zoonosis outbreak. We also propose that telephone interview at the end of reporting day is a potential improvement of the design of future contact surveys.
Collapse
Affiliation(s)
- Juanjuan Zhang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Petra Klepac
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Jonathan M Read
- Centre for Health Informatics, Computation and Statistics, Lancaster Medical School, Lancaster University, Lancashire, UK
| | - Alicia Rosello
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Xiling Wang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Shengjie Lai
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
- WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK
- Flowminder Foundation, Stockholm, Sweden
| | - Meng Li
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yujian Song
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Qingzhen Wei
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Hao Jiang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Henry Lynn
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Stefan Flasche
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Mark Jit
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK
- Modelling and Economics Unit, Public Health England, London, UK
- School of Public Health, University of Hong Kong, Hong Kong, China
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
| |
Collapse
|
6
|
Béraud G, Abrams S, Beutels P, Dervaux B, Hens N. Resurgence risk for measles, mumps and rubella in France in 2018 and 2020. ACTA ACUST UNITED AC 2019; 23. [PMID: 29945697 PMCID: PMC6152239 DOI: 10.2807/1560-7917.es.2018.23.25.1700796] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Large measles and mumps outbreaks recently occurred throughout Europe and the United States. Aim: Our aim was to estimate and map the risk of resurgence for measles, mumps and rubella in France. Methods: We used a multi-cohort model combining seroprevalence information, vaccine coverage and social contact data. Results: The overall outbreak risk for France in 2018 was highest for mumps, remained significant for measles despite a recent measles outbreak and was low for rubella. Outbreak risks were heterogeneous between departments, as the effective reproduction numbers for 2018 ranged from 1.08 to 3.66. The seroprevalence, and therefore the risk of measles and rubella infection, differed significantly between males and females. There was a lower seroprevalence, and therefore a higher risk, for males. Infants of less than 1 year would be seriously affected in a future outbreak of measles, mumps or rubella, but the highest overall caseload contribution would come from teenagers and young adults (10–25 years old). Conclusions: The high risk for teenagers and young adults is of concern in view of their vulnerability to more severe measles, mumps and rubella disease and complications.
Collapse
Affiliation(s)
- Guillaume Béraud
- Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium.,Lille University, EA2694 - Santé Publique: Epidémiologie et Qualité des Soins, Lille, France.,Médecine Interne et Maladies Infectieuses, CHU de Poitiers, Poitiers, France
| | - Steven Abrams
- Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| | - Philippe Beutels
- University of New South Wales, Faculty of Medicine, School of Public Health and Community Medicine, Sydney, Australia.,Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Benoit Dervaux
- CHU Lille, Direction de la Recherche en Santé, Lille, France.,Lille University, EA2694 - Santé Publique: Epidémiologie et Qualité des Soins, Lille, France
| | - Niel Hens
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| |
Collapse
|
7
|
Goeyvaerts N, Santermans E, Potter G, Torneri A, Van Kerckhove K, Willem L, Aerts M, Beutels P, Hens N. Household members do not contact each other at random: implications for infectious disease modelling. Proc Biol Sci 2019; 285:20182201. [PMID: 30963910 PMCID: PMC6304037 DOI: 10.1098/rspb.2018.2201] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Airborne infectious diseases such as influenza are primarily transmitted from human to human by means of social contacts, and thus easily spread within households. Epidemic models, used to gain insight into infectious disease spread and control, typically rely on the assumption of random mixing within households. Until now, there has been no direct empirical evidence to support this assumption. Here, we present the first social contact survey specifically designed to study contact networks within households. The survey was conducted in Belgium (Flanders and Brussels) from 2010 to 2011. We analysed data from 318 households totalling 1266 individuals with household sizes ranging from two to seven members. Exponential-family random graph models (ERGMs) were fitted to the within-household contact networks to reveal the processes driving contact between household members, both on weekdays and weekends. The ERGMs showed a high degree of clustering and, specifically on weekdays, decreasing connectedness with increasing household size. Furthermore, we found that the odds of a contact between older siblings and between father and child are smaller than for any other pair. The epidemic simulation results suggest that within-household contact density is the main driver of differences in epidemic spread between complete and empirical-based household contact networks. The homogeneous mixing assumption may therefore be an adequate characterization of the within-household contact structure for the purpose of epidemic simulations. However, ignoring the contact density when inferring based on an epidemic model will result in biased estimates of within-household transmission rates. Further research regarding the implementation of within-household contact networks in epidemic models is necessary.
Collapse
Affiliation(s)
- Nele Goeyvaerts
- 1 Interuniversity Institute for Biostatistics and Statistical Bioinformatics, UHasselt , Hasselt , Belgium
| | - Eva Santermans
- 1 Interuniversity Institute for Biostatistics and Statistical Bioinformatics, UHasselt , Hasselt , Belgium
| | - Gail Potter
- 2 The Emmes Corporation , Rockville, MD , USA
| | - Andrea Torneri
- 3 Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp , Antwerp , Belgium
| | - Kim Van Kerckhove
- 1 Interuniversity Institute for Biostatistics and Statistical Bioinformatics, UHasselt , Hasselt , Belgium
| | - Lander Willem
- 3 Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp , Antwerp , Belgium
| | - Marc Aerts
- 1 Interuniversity Institute for Biostatistics and Statistical Bioinformatics, UHasselt , Hasselt , Belgium
| | - Philippe Beutels
- 3 Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp , Antwerp , Belgium
| | - Niel Hens
- 1 Interuniversity Institute for Biostatistics and Statistical Bioinformatics, UHasselt , Hasselt , Belgium.,3 Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp , Antwerp , Belgium
| |
Collapse
|
8
|
Kledmanee K, Liabsuetrakul T, Sretrirutchai S. Risk of adverse pregnancy outcomes and seroprevalence for brucellosis in pregnant women exposed to goats or raw goat products in southern Thailand: a prospective cohort study. BMC Pregnancy Childbirth 2019; 19:118. [PMID: 30953474 PMCID: PMC6451268 DOI: 10.1186/s12884-019-2267-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 03/27/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Pregnant women infected with brucellosis have been shown to have higher odds of having been exposed to goats and raw goat products and adverse pregnancy outcomes. However, information on these associations in asymptomatic pregnant women is limited, particularly in the brucellosis-endemic areas. This study aimed to assess the association of a history of exposure to goats and/or raw goat products and the serological status of anti-Brucella abortus immunoglobulin G (IgG) with adverse pregnancy outcomes among pregnant women, and explore factors associated with having exposure to goats and/or raw goat products. METHODS A prospective cohort study was conducted among pregnant women from July 2015 to July 2016 at Songkhla province in southern Thailand. All pregnant women who came for antenatal care (ANC) visits were approached. Blood samples from the women who agreed to participate were randomly tested for anti-Brucella abortus IgG. The women were then followed for adverse pregnancy outcomes. RESULTS Of 666 pregnant women, the majority (74.4%) were aged 20-34 years and Muslim (89.2%), 30.6% indicated exposure to goats or raw goat products, and 17.3% had adverse pregnancy outcomes. Women rearing goats at home or having neighbors rearing goats were more likely to be exposed to goats or raw goat products by cutaneous contact. Of 465 women having a blood test, 3.7% had seropositive results for anti-Brucella abortus IgG. No association with adverse pregnancy outcomes was found in the women reporting any exposure to goat and raw goat products. Having the first ANC visit at the first trimester and history of preterm birth or low birth weight newborn were independent risk factors of adverse pregnancy outcomes. Women who had positive serological results were more likely to have a history of drinking raw goat milk than those who had negative results significantly. CONCLUSIONS Although no association between past exposure with goats and raw goat products and adverse pregnancy outcomes was found, women with past exposure showed positive anti-Brucella abortus IgG. Counseling on avoiding consumption of raw goat milk would be beneficial to prevent goat-related infection in pregnant women in this area.
Collapse
Affiliation(s)
- Kan Kledmanee
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| | - Tippawan Liabsuetrakul
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
| | - Somporn Sretrirutchai
- Department of Pathology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| |
Collapse
|
9
|
Berendes DM, Yang PJ, Lai A, Hu D, Brown J. Estimation of global recoverable human and animal fecal biomass. NATURE SUSTAINABILITY 2018; 1:679-685. [PMID: 38464867 PMCID: PMC10922008 DOI: 10.1038/s41893-018-0167-0] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 10/05/2018] [Indexed: 03/12/2024]
Abstract
Human and animal feces present persistent threats to global public health and also opportunities for recovery of resources. We present the first global-scale accounting of recoverable feces (livestock animal and human) -from 2003-2030-using country-specific human and animal population estimates and estimated species-specific feces production by human or animal body mass. We also examine global coverage of domestic livestock animals and sanitation facilities to describe the distribution of onsite vs. offsite hazards from animal and human feces. In 2014, the total mass of feces was 3.9 trillion kg/year, increasing by >52 billion kg/year since 2003 and anticipated to reach at least 4.6 trillion kg in 2030. Annual global production of feces from animals-primarily cattle, chickens, and sheep-was about four times that from humans, and ratios of animal:human feces continue to increase (geometric mean of 4.2:1 (2003) vs. 5.0:1 (2014) vs. a projected 6.0:1 (2030)). Low-income populations bear the greatest burden of onsite feces, mostly from animals in or near the domestic environment. This analysis highlights the challenges of resource recovery from concentrated and dispersed sources of feces, and the global public health policy need for safe management of animal feces.
Collapse
Affiliation(s)
- David M. Berendes
- Waterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, United States Centers for Disease Control and Prevention, Atlanta, GA, USA
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Patricia J. Yang
- School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Amanda Lai
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - David Hu
- School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Joe Brown
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| |
Collapse
|
10
|
Leung K, Jit M, Lau EHY, Wu JT. Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Sci Rep 2017. [PMID: 28801623 DOI: 10.5281/zenodo.3874808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023] Open
Abstract
The spread of many respiratory infections is determined by contact patterns between infectious and susceptible individuals in the population. There are no published data for quantifying social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong which is a hotspot for emerging infectious diseases due to its high population density and connectivity in the air transportation network. We adopted a commonly used diary-based design to conduct a social contact survey in Hong Kong in 2015/16 using both paper and online questionnaires. Participants using paper questionnaires reported more contacts and longer contact duration than those using online questionnaires. Participants reported 13 person-hours of contact and 8 contacts per day on average, which decreased over age but increased with household size, years of education and income level. Prolonged and frequent contacts, and contacts at home, school and work were more likely to involve physical contacts. Strong age-assortativity was observed in all age groups. We evaluated the characteristics of social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Our findings could help to improve the design of future social contact surveys, parameterize transmission models of respiratory infectious diseases, and inform intervention strategies based on model outputs.
Collapse
Affiliation(s)
- Kathy Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Mark Jit
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Modelling and Economics Unit, Public Health England, London, United Kingdom
| | - Eric H Y Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Joseph T Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China.
| |
Collapse
|
11
|
Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Sci Rep 2017; 7:7974. [PMID: 28801623 PMCID: PMC5554254 DOI: 10.1038/s41598-017-08241-1] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 07/10/2017] [Indexed: 11/08/2022] Open
Abstract
The spread of many respiratory infections is determined by contact patterns between infectious and susceptible individuals in the population. There are no published data for quantifying social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong which is a hotspot for emerging infectious diseases due to its high population density and connectivity in the air transportation network. We adopted a commonly used diary-based design to conduct a social contact survey in Hong Kong in 2015/16 using both paper and online questionnaires. Participants using paper questionnaires reported more contacts and longer contact duration than those using online questionnaires. Participants reported 13 person-hours of contact and 8 contacts per day on average, which decreased over age but increased with household size, years of education and income level. Prolonged and frequent contacts, and contacts at home, school and work were more likely to involve physical contacts. Strong age-assortativity was observed in all age groups. We evaluated the characteristics of social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Our findings could help to improve the design of future social contact surveys, parameterize transmission models of respiratory infectious diseases, and inform intervention strategies based on model outputs.
Collapse
|
12
|
Kifle YW, Goeyvaerts N, Van Kerckhove K, Willem L, Kucharski A, Faes C, Leirs H, Hens N, Beutels P. Correction: Animal Ownership and Touching Enrich the Context of Social Contacts Relevant to the Spread of Human Infectious Diseases. PLoS One 2016; 11:e0148718. [PMID: 26840638 PMCID: PMC4739693 DOI: 10.1371/journal.pone.0148718] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
|