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Pascoe L, Clemen T, Bradshaw K, Nyambo D. Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15578. [PMID: 36497652 PMCID: PMC9740748 DOI: 10.3390/ijerph192315578] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/20/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
The study sought to review the works of literature on agent-based modeling and the influence of climatic and environmental factors on disease outbreak, transmission, and surveillance. Thus, drawing the influence of environmental variables such as vegetation index, households, mosquito habitats, breeding sites, and climatic variables including precipitation or rainfall, temperature, wind speed, and relative humidity on dengue disease modeling using the agent-based model in an African context and globally was the aim of the study. A search strategy was developed and used to search for relevant articles from four databases, namely, PubMed, Scopus, Research4Life, and Google Scholar. Inclusion criteria were developed, and 20 articles met the criteria and have been included in the review. From the reviewed works of literature, the study observed that climatic and environmental factors may influence the arbovirus disease outbreak, transmission, and surveillance. Thus, there is a call for further research on the area. To benefit from arbovirus modeling, it is crucial to consider the influence of climatic and environmental factors, especially in Africa, where there are limited studies exploring this phenomenon.
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Affiliation(s)
- Luba Pascoe
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
| | - Thomas Clemen
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
- Department of Computer Science, Hamburg University of Applied Sciences, Berliner Tor 7, 20099 Hamburg, Germany
| | - Karen Bradshaw
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
- Department of Computer Science, Rhodes University, Grahamstown 6139, South Africa
| | - Devotha Nyambo
- Nelson Mandela African Institution of Science and Technology, Arusha P.O Box 447, Tanzania
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Tabasi M, Alesheikh AA, Sofizadeh A, Saeidian B, Pradhan B, AlAmri A. A spatio-temporal agent-based approach for modeling the spread of zoonotic cutaneous leishmaniasis in northeast Iran. Parasit Vectors 2020; 13:572. [PMID: 33176858 PMCID: PMC7659076 DOI: 10.1186/s13071-020-04447-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 10/30/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Zoonotic cutaneous leishmaniasis (ZCL) is a neglected tropical disease worldwide, especially the Middle East. Although previous works attempt to model the ZCL spread using various environmental factors, the interactions between vectors (Phlebotomus papatasi), reservoir hosts, humans, and the environment can affect its spread. Considering all of these aspects is not a trivial task. METHODS An agent-based model (ABM) is a relatively new approach that provides a framework for analyzing the heterogeneity of the interactions, along with biological and environmental factors in such complex systems. The objective of this research is to design and develop an ABM that uses Geospatial Information System (GIS) capabilities, biological behaviors of vectors and reservoir hosts, and an improved Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model to explore the spread of ZCL. Various scenarios were implemented to analyze the future ZCL spreads in different parts of Maraveh Tappeh County, in the northeast region of Golestan Province in northeastern Iran, with alternative socio-ecological conditions. RESULTS The results confirmed that the spread of the disease arises principally in the desert, low altitude areas, and riverside population centers. The outcomes also showed that the restricting movement of humans reduces the severity of the transmission. Moreover, the spread of ZCL has a particular temporal pattern, since the most prevalent cases occurred in the fall. The evaluation test also showed the similarity between the results and the reported spatiotemporal trends. CONCLUSIONS This study demonstrates the capability and efficiency of ABM to model and predict the spread of ZCL. The results of the presented approach can be considered as a guide for public health management and controlling the vector population .
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Affiliation(s)
- Mohammad Tabasi
- Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, 19967 15433 Iran
| | - Ali Asghar Alesheikh
- Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, 19967 15433 Iran
| | - Aioub Sofizadeh
- Infectious Diseases Research Center, Golestan University of Medical Sciences, Gorgan, Iran
| | - Bahram Saeidian
- The Centre for Spatial Data Infrastructures and Land Administration (CSDILA), Department of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC 3010 Australia
| | - Biswajeet Pradhan
- The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia
- Department of Energy and Mineral Resources Engineering, Sejong University, Choongmu-gwan, 209, Neungdong-ro, Gwangin-gu, Seoul, 05006 Korea
- Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, UKM, 43600 Bangi, Selangor Malaysia
| | - Abdullah AlAmri
- Department of Geology & Geophysics, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451 Saudi Arabia
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Feng X, Huo X, Tang B, Tang S, Wang K, Wu J. Modelling and Analyzing Virus Mutation Dynamics of Chikungunya Outbreaks. Sci Rep 2019; 9:2860. [PMID: 30814598 PMCID: PMC6393467 DOI: 10.1038/s41598-019-38792-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 01/09/2019] [Indexed: 11/09/2022] Open
Abstract
Chikungunya fever, caused by chikungunya virus (CHIKV) and transmitted to humans by infected Aedes mosquitoes, has posed a global threat in several countries in 2015. Recent outbreaks in La Réunion, Italy and China are related with a new variant of CHIKV with shorter extrinsic incubation period in contaminated mosquitoes, but the role of this new variant on the spread of chikungunya fever is unclear. We develop a mathematical model that incorporates the virus mutation dynamics in the transmission of CHIKV among mosquitoes and humans. Our numerical simulations show that a substantial virus mutation rate combined with high virus transmission probabilities from mosquito to human, could result in sustainable chikungunya fever outbreaks. Further, we apply Markov Chain Monte Carlo sampling method to fit our model to the 2007 chikungunya fever outbreak data in North-Eastern Italy where the mutant strain was detected. We conclude that the basic reproduction number might be underestimated without considering the mutation dynamics, and our estimation shows that the basic reproduction number of the 2007 Italy outbreak was [Formula: see text] = 2.035[95%Cl: 1.9424 - 2.1366]. Sensitivity analysis shows that the transmission rate of the mutant strain from mosquitoes to human is more influential on [Formula: see text] than the shortened extrinsic incubation period. We conclude that the virus mutation dynamics could play an important role in the transmission of CHIKV, and there is a crucial need to better understand the mutation mechanism.
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Affiliation(s)
- Xiaomei Feng
- School of mathematics and information sciences, Shaanxi Normal University, Xi'an, 710062, People's Republic of China
- School of mathematics and information technology, Yuncheng University, Yuncheng, 044000, People's Republic of China
| | - Xi Huo
- Department of Mathematics, University of Miami, Coral Gables, FL, 33124-4250, USA
| | - Biao Tang
- Laboratory for Industrial and Applied Mathematics, Faculty of Sciences, York University, Toronto, ON, M3J1P3, Canada
| | - Sanyi Tang
- School of mathematics and information sciences, Shaanxi Normal University, Xi'an, 710062, People's Republic of China
| | - Kai Wang
- Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830011, People's Republic of China
| | - Jianhong Wu
- Laboratory for Industrial and Applied Mathematics, Faculty of Sciences, York University, Toronto, ON, M3J1P3, Canada.
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Kao YH, Eisenberg MC. Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment. Epidemics 2018; 25:89-100. [PMID: 29903539 PMCID: PMC6264791 DOI: 10.1016/j.epidem.2018.05.010] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 05/18/2018] [Accepted: 05/24/2018] [Indexed: 12/25/2022] Open
Abstract
Mathematical modeling has an extensive history in vector-borne disease epidemiology, and is increasingly used for prediction, intervention design, and understanding mechanisms. Many studies rely on parameter estimation to link models and data, and to tailor predictions and counterfactuals to specific settings. However, few studies have formally evaluated whether vector-borne disease models can properly estimate the parameters of interest given the constraints of a particular dataset. Identifiability analysis allows us to examine whether model parameters can be estimated uniquely-a lack of consideration of such issues can result in misleading or incorrect parameter estimates and model predictions. Here, we evaluate both structural (theoretical) and practical identifiability of a commonly used compartmental model of mosquito-borne disease, using the 2010 dengue epidemic in Taiwan as a case study. We show that while the model is structurally identifiable, it is practically unidentifiable under a range of human and mosquito time series measurement scenarios. In particular, the transmission parameters form a practically identifiable combination and thus cannot be estimated separately, potentially leading to incorrect predictions of the effects of interventions. However, in spite of the unidentifiability of the individual parameters, the basic reproduction number was successfully estimated across the unidentifiable parameter ranges. These identifiability issues can be resolved by directly measuring several additional human and mosquito life-cycle parameters both experimentally and in the field. While we only consider the simplest case for the model, we show that a commonly used model of vector-borne disease is unidentifiable from human and mosquito incidence data, making it difficult or impossible to estimate parameters or assess intervention strategies. This work illustrates the importance of examining identifiability when linking models with data to make predictions and inferences, and particularly highlights the importance of combining laboratory, field, and case data if we are to successfully estimate epidemiological and ecological parameters using models.
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Affiliation(s)
- Yu-Han Kao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States
| | - Marisa C Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States; Department of Mathematics, University of Michigan, Ann Arbor, MI, United States.
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Dias JCA, Monteiro LHA. Clustered Breeding Sites: Shelters for Vector-Borne Diseases. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2018; 2018:2575017. [PMID: 30112017 PMCID: PMC6077366 DOI: 10.1155/2018/2575017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Accepted: 06/03/2018] [Indexed: 11/17/2022]
Abstract
Here, the propagation of vector-borne diseases is modeled by using a probabilistic cellular automaton. Numerical simulations considering distinct spatial distributions and time variations of the vector abundance are performed, in order to investigate their impacts on the number of infected individuals of the host population. The main conclusion is as follows: in the clustered distributions, the prevalence is lower, but the eradication is more difficult to be achieved, as compared to homogeneous distributions. This result can be relevant in the implementation of preventive surveillance measures.
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Affiliation(s)
- J. C. A. Dias
- Universidade Presbiteriana Mackenzie, PPGEEC, São Paulo, SP, Brazil
| | - L. H. A. Monteiro
- Universidade Presbiteriana Mackenzie, PPGEEC, São Paulo, SP, Brazil
- Universidade de São Paulo, Escola Politécnica, São Paulo, SP, Brazil
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Stone CM, Schwab SR, Fonseca DM, Fefferman NH. Human movement, cooperation and the effectiveness of coordinated vector control strategies. J R Soc Interface 2018; 14:rsif.2017.0336. [PMID: 28855386 DOI: 10.1098/rsif.2017.0336] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 08/03/2017] [Indexed: 12/22/2022] Open
Abstract
Vector-borne disease transmission is often typified by highly focal transmission and influenced by movement of hosts and vectors across different scales. The ecological and environmental conditions (including those created by humans through vector control programmes) that result in metapopulation dynamics remain poorly understood. The development of control strategies that would most effectively limit outbreaks given such dynamics is particularly urgent given the recent epidemics of dengue, chikungunya and Zika viruses. We developed a stochastic, spatial model of vector-borne disease transmission, allowing for movement of hosts between patches. Our model is applicable to arbovirus transmission by Aedes aegypti in urban settings and was parametrized to capture Zika virus transmission in particular. Using simulations, we investigated the extent to which two aspects of vector control strategies are affected by human commuting patterns: the extent of coordination and cooperation between neighbouring communities. We find that transmission intensity is highest at intermediate levels of host movement. The extent to which coordination of control activities among neighbouring patches decreases the prevalence of infection is affected by both how frequently humans commute and the proportion of neighbouring patches that commits to vector surveillance and control activities. At high levels of host movement, patches that do not contribute to vector control may act as sources of infection in the landscape, yet have comparable levels of prevalence as patches that do cooperate. This result suggests that real cooperation among neighbours will be critical to the development of effective pro-active strategies for vector-borne disease control in today's commuter-linked communities.
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Affiliation(s)
- Chris M Stone
- Illinois Natural History Survey, University of Illinois at Urbana-Champaign, Champaign, IL, USA .,Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, USA
| | - Samantha R Schwab
- Program in Ecology and Evolutionary Biology, Rutgers University, New Brunswick, NJ, USA
| | - Dina M Fonseca
- Center for Vector Biology, Rutgers University, New Brunswick, NJ, USA
| | - Nina H Fefferman
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, USA
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Schmidt CA, Comeau G, Monaghan AJ, Williamson DJ, Ernst KC. Effects of desiccation stress on adult female longevity in Aedes aegypti and Ae. albopictus (Diptera: Culicidae): results of a systematic review and pooled survival analysis. Parasit Vectors 2018; 11:267. [PMID: 29695282 PMCID: PMC5918765 DOI: 10.1186/s13071-018-2808-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 03/25/2018] [Indexed: 11/21/2022] Open
Abstract
Background Transmission dynamics of mosquito-borne viruses such as dengue, Zika and chikungunya are affected by the longevity of the adult female mosquito. Environmental conditions influence the survival of adult female Aedes mosquitoes, the primary vectors of these viruses. While the association of temperature with Aedes mortality has been relatively well-explored, the role of humidity is less established. The current study’s goals were to compile knowledge of the influence of humidity on adult survival in the important vector species Aedes aegypti and Ae. albopictus, and to quantify this relationship while accounting for the modifying effect of temperature. Methods We performed a systematic literature review to identify studies reporting experimental results informing the relationships among temperature, humidity and adult survival in Ae. aegypti and Ae. albopictus. Using a novel simulation approach to harmonize disparate survival data, we conducted pooled survival analyses via stratified and mixed effects Cox regression to estimate temperature-dependent associations between humidity and mortality risk for these species across a broad range of temperatures and vapor pressure deficits. Results After screening 1517 articles, 17 studies (one in semi-field and 16 in laboratory settings) met inclusion criteria and collectively reported results for 192 survival experiments. We review and synthesize relevant findings from these studies. Our stratified model estimated a strong temperature-dependent association of humidity with mortality in both species, though associations were not significant for Ae. albopictus in the mixed effects model. Lowest mortality risks were estimated around 27.5 °C and 21.5 °C for Ae. aegypti and Ae. albopictus, respectively, and mortality increased non-linearly with decreasing humidity. Aedes aegypti had a survival advantage relative to Ae. albopictus in the stratified model under most conditions, but species differences were not significant in the mixed effects model. Conclusions Humidity is associated with mortality risk in adult female Ae. aegypti in controlled settings. Data are limited at low humidities, temperature extremes, and for Ae. albopictus, and further studies should be conducted to reduce model uncertainty in these contexts. Desiccation is likely an important factor in Aedes population dynamics and viral transmission in arid regions. Models of Aedes-borne virus transmission may be improved by more comprehensively representing humidity effects. Electronic supplementary material The online version of this article (10.1186/s13071-018-2808-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Chris A Schmidt
- Department of Epidemiology and Biostatistics, Mel & Enid Zuckerman College of Public Health, University of Arizona, 1295 N. Martin Ave, Tucson, AZ, 85724, USA. .,National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO, 80307, USA.
| | - Genevieve Comeau
- Department of Entomology, College of Agriculture & Life Sciences, University of Arizona, P.O. Box 210036, Tucson, AZ, 85721, USA
| | - Andrew J Monaghan
- National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO, 80307, USA
| | - Daniel J Williamson
- Department of Entomology, College of Agriculture & Life Sciences, University of Arizona, P.O. Box 210036, Tucson, AZ, 85721, USA
| | - Kacey C Ernst
- Department of Epidemiology and Biostatistics, Mel & Enid Zuckerman College of Public Health, University of Arizona, 1295 N. Martin Ave, Tucson, AZ, 85724, USA.,Department of Entomology, College of Agriculture & Life Sciences, University of Arizona, P.O. Box 210036, Tucson, AZ, 85721, USA
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Wiratsudakul A, Suparit P, Modchang C. Dynamics of Zika virus outbreaks: an overview of mathematical modeling approaches. PeerJ 2018; 6:e4526. [PMID: 29593941 PMCID: PMC5866925 DOI: 10.7717/peerj.4526] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 03/02/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The Zika virus was first discovered in 1947. It was neglected until a major outbreak occurred on Yap Island, Micronesia, in 2007. Teratogenic effects resulting in microcephaly in newborn infants is the greatest public health threat. In 2016, the Zika virus epidemic was declared as a Public Health Emergency of International Concern (PHEIC). Consequently, mathematical models were constructed to explicitly elucidate related transmission dynamics. SURVEY METHODOLOGY In this review article, two steps of journal article searching were performed. First, we attempted to identify mathematical models previously applied to the study of vector-borne diseases using the search terms "dynamics," "mathematical model," "modeling," and "vector-borne" together with the names of vector-borne diseases including chikungunya, dengue, malaria, West Nile, and Zika. Then the identified types of model were further investigated. Second, we narrowed down our survey to focus on only Zika virus research. The terms we searched for were "compartmental," "spatial," "metapopulation," "network," "individual-based," "agent-based" AND "Zika." All relevant studies were included regardless of the year of publication. We have collected research articles that were published before August 2017 based on our search criteria. In this publication survey, we explored the Google Scholar and PubMed databases. RESULTS We found five basic model architectures previously applied to vector-borne virus studies, particularly in Zika virus simulations. These include compartmental, spatial, metapopulation, network, and individual-based models. We found that Zika models carried out for early epidemics were mostly fit into compartmental structures and were less complicated compared to the more recent ones. Simple models are still commonly used for the timely assessment of epidemics. Nevertheless, due to the availability of large-scale real-world data and computational power, recently there has been growing interest in more complex modeling frameworks. DISCUSSION Mathematical models are employed to explore and predict how an infectious disease spreads in the real world, evaluate the disease importation risk, and assess the effectiveness of intervention strategies. As the trends in modeling of infectious diseases have been shifting towards data-driven approaches, simple and complex models should be exploited differently. Simple models can be produced in a timely fashion to provide an estimation of the possible impacts. In contrast, complex models integrating real-world data require more time to develop but are far more realistic. The preparation of complicated modeling frameworks prior to the outbreaks is recommended, including the case of future Zika epidemic preparation.
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Affiliation(s)
- Anuwat Wiratsudakul
- Department of Clinical Sciences and Public Health, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand
- The Monitoring and Surveillance Center for Zoonotic Diseases in Wildlife and Exotic Animals, Faculty of Veterinary Science, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand
| | - Parinya Suparit
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Ratchathewi, Bangkok, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Ratchathewi, Bangkok, Thailand
- Centre of Excellence in Mathematics, CHE, Ratchathewi, Bangkok, Thailand
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Huang Q, Hu L, Liao QB, Xia J, Wang QR, Peng HJ. Spatiotemporal Analysis of the Malaria Epidemic in Mainland China, 2004-2014. Am J Trop Med Hyg 2017; 97:504-513. [PMID: 28829728 DOI: 10.4269/ajtmh.16-0711] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The purpose of this study is to characterize spatiotemporal heterogeneities in malaria distribution at a provincial level and investigate the association between malaria incidence and climate factors from 2004 to 2014 in China to inform current malaria control efforts. National malaria incidence peaked (4.6/100,000) in 2006 and decreased to a very low level (0.21/100,000) in 2014, and the proportion of imported cases increased from 16.2% in 2004 to 98.2% in 2014. Statistical analyses of global and local spatial autocorrelations and purely spatial scan statistics revealed that malaria was localized in Hainan, Anhui, and Yunnan during 2004-2009 and then gradually shifted and clustered in Yunnan after 2010. Purely temporal clusters shortened to less than 5 months during 2012-2014. The two most likely clusters detected using spatiotemporal analysis occurred in Anhui between July 2005 and November 2007 and Yunnan between January 2010 and June 2012. Correlation coefficients for the association between malaria incidence and climate factors sharply decreased after 2010, and there were zero-month lag effects for climate factors during 2010-2014. Overall, the spatiotemporal distribution of malaria in China changed from relatively scattered (2004-2009) to relatively clustered (2010-2014). As the proportion of imported cases increased, the effect of climate factors on malaria incidence has gradually become weaker since 2011. Therefore, new warning systems should be applied to monitor resurgence and outbreaks of malaria in mainland China, and quarantine at borders should be reinforced to control the increasingly trend of imported malaria cases.
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Affiliation(s)
- Qiang Huang
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Lin Hu
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Qi-Bin Liao
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jing Xia
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Qian-Ru Wang
- Department of Atmospheric Science, College of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, Sichuan, China
| | - Hong-Juan Peng
- Department of Pathogen Biology, Guangdong Provincial Key Laboratory of Tropical Disease Research, and Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes, School of Public Health, Southern Medical University, Guangzhou, Guangdong Province, China
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Willem L, Verelst F, Bilcke J, Hens N, Beutels P. Lessons from a decade of individual-based models for infectious disease transmission: a systematic review (2006-2015). BMC Infect Dis 2017; 17:612. [PMID: 28893198 PMCID: PMC5594572 DOI: 10.1186/s12879-017-2699-8] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Accepted: 08/22/2017] [Indexed: 02/18/2023] Open
Abstract
Background Individual-based models (IBMs) are useful to simulate events subject to stochasticity and/or heterogeneity, and have become well established to model the potential (re)emergence of pathogens (e.g., pandemic influenza, bioterrorism). Individual heterogeneity at the host and pathogen level is increasingly documented to influence transmission of endemic diseases and it is well understood that the final stages of elimination strategies for vaccine-preventable childhood diseases (e.g., polio, measles) are subject to stochasticity. Even so it appears IBMs for both these phenomena are not well established. We review a decade of IBM publications aiming to obtain insights in their advantages, pitfalls and rationale for use and to make recommendations facilitating knowledge transfer within and across disciplines. Methods We systematically identified publications in Web of Science and PubMed from 2006-2015 based on title/abstract/keywords screening (and full-text if necessary) to retrieve topics, modeling purposes and general specifications. We extracted detailed modeling features from papers on established vaccine-preventable childhood diseases based on full-text screening. Results We identified 698 papers, which applied an IBM for infectious disease transmission, and listed these in a reference database, describing their general characteristics. The diversity of disease-topics and overall publication frequency have increased over time (38 to 115 annual publications from 2006 to 2015). The inclusion of intervention strategies (8 to 52) and economic consequences (1 to 20) are increasing, to the detriment of purely theoretical explorations. Unfortunately, terminology used to describe IBMs is inconsistent and ambiguous. We retrieved 24 studies on a vaccine-preventable childhood disease (covering 7 different diseases), with publication frequency increasing from the first such study published in 2008. IBMs have been useful to explore heterogeneous between- and within-host interactions, but combined applications are still sparse. The amount of missing information on model characteristics and study design is remarkable. Conclusions IBMs are suited to combine heterogeneous within- and between-host interactions, which offers many opportunities, especially to analyze targeted interventions for endemic infections. We advocate the exchange of (open-source) platforms and stress the need for consistent “branding”. Using (existing) conventions and reporting protocols would stimulate cross-fertilization between research groups and fields, and ultimately policy making in decades to come. Electronic supplementary material The online version of this article (doi:10.1186/s12879-017-2699-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Lander Willem
- Centre for Health Economics Research & Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
| | - Frederik Verelst
- Centre for Health Economics Research & Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Joke Bilcke
- Centre for Health Economics Research & Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Niel Hens
- Centre for Health Economics Research & Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,Interuniversity Institute for Biostatistics and statistical Bioinformatics, UHasselt, Hasselt, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research & Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.,School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia
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Erguler K, Chandra NL, Proestos Y, Lelieveld J, Christophides GK, Parham PE. A large-scale stochastic spatiotemporal model for Aedes albopictus-borne chikungunya epidemiology. PLoS One 2017; 12:e0174293. [PMID: 28362820 PMCID: PMC5375158 DOI: 10.1371/journal.pone.0174293] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 03/07/2017] [Indexed: 12/17/2022] Open
Abstract
Chikungunya is a viral disease transmitted to humans primarily via the bites of infected Aedes mosquitoes. The virus caused a major epidemic in the Indian Ocean in 2004, affecting millions of inhabitants, while cases have also been observed in Europe since 2007. We developed a stochastic spatiotemporal model of Aedes albopictus-borne chikungunya transmission based on our recently developed environmentally-driven vector population dynamics model. We designed an integrated modelling framework incorporating large-scale gridded climate datasets to investigate disease outbreaks on Reunion Island and in Italy. We performed Bayesian parameter inference on the surveillance data, and investigated the validity and applicability of the underlying biological assumptions. The model successfully represents the outbreak and measures of containment in Italy, suggesting wider applicability in Europe. In its current configuration, the model implies two different viral strains, thus two different outbreaks, for the two-stage Reunion Island epidemic. Characterisation of the posterior distributions indicates a possible relationship between the second larger outbreak on Reunion Island and the Italian outbreak. The model suggests that vector control measures, with different modes of operation, are most effective when applied in combination: adult vector intervention has a high impact but is short-lived, larval intervention has a low impact but is long-lasting, and quarantining infected territories, if applied strictly, is effective in preventing large epidemics. We present a novel approach in analysing chikungunya outbreaks globally using a single environmentally-driven mathematical model. Our study represents a significant step towards developing a globally applicable Ae. albopictus-borne chikungunya transmission model, and introduces a guideline for extending such models to other vector-borne diseases.
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Affiliation(s)
- Kamil Erguler
- Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
- * E-mail: (KE); (PEP)
| | - Nastassya L. Chandra
- Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College London, London W2 1PG, United Kingdom
| | - Yiannis Proestos
- Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
| | - Jos Lelieveld
- Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
- Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, D-55128 Mainz, Germany
| | - George K. Christophides
- Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- Computation-based Science and Technology Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
| | - Paul E. Parham
- Department of Public Health and Policy, Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 3GL, United Kingdom
- * E-mail: (KE); (PEP)
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12
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Chadsuthi S, Iamsirithaworn S, Triampo W, Cummings DAT. The impact of rainfall and temperature on the spatial progression of cases during the chikungunya re-emergence in Thailand in 2008-2009. Trans R Soc Trop Med Hyg 2016; 110:125-33. [PMID: 26822605 DOI: 10.1093/trstmh/trv114] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND In 2008, chikungunya virus (CHIKV) re-emerged in Thailand after more than a decade of absence. Cases first appeared in the extreme southern region of the country and advanced northward approx. 300 km over the next 18 months. The spatial advance of CHIKV cases appeared to occur at two rates, initially progressing slowly and then increasing in speed. We hypothesize that climatic variation affected the transmission of CHIKV in the country. METHODS To determine the effect of climate on CHIKV transmission, we evaluated models where climate affects the transmission rate from mosquitoes to humans; extrinsic incubation period; fertility rate of mosquitoes; and the mortality rate of mosquito larvae. We compared these models to models that did not include climate effects. RESULTS The inclusion of climate data greatly improved model fit with models assuming climate affected the fertility rate of mosquitoes providing the best fit to data. CONCLUSION These results suggest that climatic variation contributed to the slower rate of incidence observed in March 2009. Overall, a gradient in transmission probability and mortality and fertility rates of mosquito is observed over the entire area with the most southern districts experiencing the most efficient transmission.
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Affiliation(s)
- Sudarat Chadsuthi
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Rama VI, Bangkok 10400, Thailand
| | - Sopon Iamsirithaworn
- Department of Disease Control, Ministry of Public Health, Tivanond 9 Road, Nonthaburi, 11000, Thailand
| | - Wannapong Triampo
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Rama VI, Bangkok 10400, Thailand ThEP Center, CHE, 328 Si Ayutthaya Road, Bangkok 10400, Thailand Centre of Excellence in Mathematics CHE, Sriayudhaya Rd., Bangkok 10400, Thailand
| | - Derek A T Cummings
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, 21205 USA Department of Biology, University of Florida, Gainesville, FL 32611, USA
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13
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Climate Change and Health in the Urban Context. INTERNATIONAL JOURNAL OF HEALTH SERVICES 2016; 46:389-405. [DOI: 10.1177/0020731416643444] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Climate change poses huge challenges for public health, and cities are at the forefront of this process. The purpose of this paper is to present the issues climate change poses for public health in the city of Barcelona, how they are being addressed, and what are the current major challenges, trying to contribute to the development of a baseline understanding of the status of adaptation in cities from a public health perspective. The major issues related to climate change faced by the city are common to other urban centers in a Mediterranean climate: heat waves, water availability and quality, air quality, and diseases transmitted by vectors, and all are reviewed in detail with empirical data. They are not a potential threat for the future, but have actually challenged the city services and infrastructure over the last years, requiring sustainable responses and rigorous planning.
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Sam IC, Kümmerer BM, Chan YF, Roques P, Drosten C, AbuBakar S. Updates on chikungunya epidemiology, clinical disease, and diagnostics. Vector Borne Zoonotic Dis 2016; 15:223-30. [PMID: 25897809 DOI: 10.1089/vbz.2014.1680] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Chikungunya virus (CHIKV) is an Aedes-borne alphavirus, historically found in Africa and Asia, where it caused sporadic outbreaks. In 2004, CHIKV reemerged in East Africa and spread globally to cause epidemics, including, for the first time, autochthonous transmission in Europe, the Middle East, and Oceania. The epidemic strains were of the East/Central/South African genotype. Strains of the Asian genotype of CHIKV continued to cause outbreaks in Asia and spread to Oceania and, in 2013, to the Americas. Acute disease, mainly comprising fever, rash, and arthralgia, was previously regarded as self-limiting; however, there is growing evidence of severe but rare manifestations, such as neurological disease. Furthermore, CHIKV appears to cause a significant burden of long-term morbidity due to persistent arthralgia. Diagnostic assays have advanced greatly in recent years, although there remains a need for simple, accurate, and affordable tests for the developing countries where CHIKV is most prevalent. This review focuses on recent important work on the epidemiology, clinical disease and diagnostics of CHIKV.
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Affiliation(s)
- I-Ching Sam
- 1 Department of Medical Microbiology, Faculty of Medicine, University Malaya , Kuala Lumpur, Malaysia
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15
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Dengue and chikungunya: modelling the expansion of mosquito-borne viruses into naïve populations. Parasitology 2016; 143:860-873. [PMID: 27045211 DOI: 10.1017/s0031182016000421] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
With the recent global spread of a number of mosquito-borne viruses, there is an urgent need to understand the factors that contribute to the ability of viruses to expand into naïve populations. Using dengue and chikungunya viruses as case studies, we detail the necessary components of the expansion process: presence of the mosquito vector; introduction of the virus; and suitable conditions for local transmission. For each component we review the existing modelling approaches that have been used to understand recent emergence events or to assess the risk of future expansions. We identify gaps in our knowledge that are related to each of the distinct aspects of the human-mosquito transmission cycle: mosquito ecology; human-mosquito contact; mosquito-virus interactions; and human-virus interactions. Bridging these gaps poses challenges to both modellers and empiricists, but only through further integration of models and data will we improve our ability to better understand, and ultimately control, several infectious diseases that exert a significant burden on human health.
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16
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González-Parra G, Villanueva RJ, Ruiz-Baragaño J, Moraño JA. Modelling influenza A(H1N1) 2009 epidemics using a random network in a distributed computing environment. Acta Trop 2015; 143:29-35. [PMID: 25559047 DOI: 10.1016/j.actatropica.2014.12.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Revised: 12/10/2014] [Accepted: 12/17/2014] [Indexed: 01/11/2023]
Abstract
In this paper we propose the use of a random network model for simulating and understanding the epidemics of influenza A(H1N1). The proposed model is used to simulate the transmission process of influenza A(H1N1) in a community region of Venezuela using distributed computing in order to accomplish many realizations of the underlying random process. These large scale epidemic simulations have recently become an important application of high-performance computing. The network model proposed performs better than the traditional epidemic model based on ordinary differential equations since it adjusts better to the irregularity of the real world data. In addition, the network model allows the consideration of many possibilities regarding the spread of influenza at the population level. The results presented here show how well the SEIR model fits the data for the AH1N1 time series despite the irregularity of the data and returns parameter values that are in good agreement with the medical data regarding AH1N1 influenza virus. This versatile network model approach may be applied to the simulation of the transmission dynamics of several epidemics in human networks. In addition, the simulation can provide useful information for the understanding, prediction and control of the transmission of influenza A(H1N1) epidemics.
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Affiliation(s)
- Gilberto González-Parra
- Grupo Matemática Multidisciplinar, Fac. Ingeniería Universidad de los Andes, Venezuela; Centro de Investigaciones en Matemática Aplicada (CIMA), Universidad de los Andes, Venezuela.
| | - Rafael-J Villanueva
- Instituto de Matemática Multidisciplinar, Universitat Politécnica de Valéncia, Edificio 8G, 2°, 46022 Valencia, Spain
| | - Javier Ruiz-Baragaño
- Instituto de Matemática Multidisciplinar, Universitat Politécnica de Valéncia, Edificio 8G, 2°, 46022 Valencia, Spain
| | - Jose-A Moraño
- Instituto de Matemática Multidisciplinar, Universitat Politécnica de Valéncia, Edificio 8G, 2°, 46022 Valencia, Spain
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Stolk WA, Stone C, de Vlas SJ. Modelling lymphatic filariasis transmission and control: modelling frameworks, lessons learned and future directions. ADVANCES IN PARASITOLOGY 2015; 87:249-91. [PMID: 25765197 DOI: 10.1016/bs.apar.2014.12.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Mathematical modelling provides a useful tool for policy making and planning in lymphatic filariasis control programmes, by providing trend forecasts based on sound scientific knowledge and principles. This is now especially true, in view of the ambitious target to eliminate lymphatic filariasis as a public health problem globally by the year 2020 and the short remaining timeline to achieve this. To meet this target, elimination programmes need to be accelerated, requiring further optimization of strategies and tailoring to local circumstances. Insights from epidemiological transmission models provide a useful basis. Two general models of lymphatic filariasis transmission and control are nowadays in use to support decision-making, namely a population-based deterministic model (EPIFIL) and an individual-based stochastic model (LYMFASIM). Model predictions confirm that lymphatic filariasis transmission can be interrupted by annual mass drug administration (MDA), but this may need to be continued much longer than the initially suggested 4-6 years in areas with high transmission intensity or poor treatment coverage. However, the models have not been validated against longitudinal data describing the impact of MDA programmes. Some critical issues remain to be incorporated in one or both of the models to make predictions on elimination more realistic, including the possible occurrence of systematic noncompliance, the risk of emerging parasite resistance to anthelmintic drugs, and spatial heterogeneities. Rapid advances are needed to maximize the utility of models in decision-making for the ongoing ambitious lymphatic filariasis elimination programmes.
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Affiliation(s)
- Wilma A Stolk
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands
| | - Chris Stone
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
| | - Sake J de Vlas
- Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands
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18
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Christofferson RC, Chisenhall DM, Wearing HJ, Mores CN. Chikungunya viral fitness measures within the vector and subsequent transmission potential. PLoS One 2014; 9:e110538. [PMID: 25310016 PMCID: PMC4195746 DOI: 10.1371/journal.pone.0110538] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Accepted: 09/06/2014] [Indexed: 12/23/2022] Open
Abstract
Given the recent emergence of chikungunya in the Americas, the accuracy of forecasting and prediction of chikungunya transmission potential in the U.S. requires urgent assessment. The La Reunion-associated sub-lineage of chikungunya (with a valine substitution in the envelope protein) was shown to increase viral fitness in the secondary vector, Ae. albopictus. Subsequently, a majority of experimental and modeling efforts focused on this combination of a sub-lineage of the East-Central-South African genotype (ECSA-V) – Ae. albopictus, despite the Asian genotype being the etiologic agent of recent chikungunya outbreaks world-wide. We explore a collection of data to investigate relative transmission efficiencies of the three major genotypes/sub-lineages of chikungunya and found difference in the extrinsic incubation periods to be largely overstated. However, there is strong evidence supporting the role of Ae. albopictus in the expansion of chikungunya that our R0 calculations cannot attribute to fitness increases in one vector over another. This suggests other ecological factors associated with the Ae. albopictus-ECSA-V cycle may drive transmission intensity differences. With the apparent bias in literature, however, we are less prepared to evaluate transmission where Ae. aegypti plays a significant role. Holistic investigations of CHIKV transmission cycle(s) will allow for more complete assessment of transmission risk in areas affected by either or both competent vectors.
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Affiliation(s)
- Rebecca C. Christofferson
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana, United States of America
- * E-mail:
| | - Daniel M. Chisenhall
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana, United States of America
| | - Helen J. Wearing
- Department of Biology, The University of New Mexico, Albuquerque, New Mexico, United States of America
- Department of Mathematics & Statistics, The University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Christopher N. Mores
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana, United States of America
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Robinson M, Conan A, Duong V, Ly S, Ngan C, Buchy P, Tarantola A, Rodó X. A model for a chikungunya outbreak in a rural Cambodian setting: implications for disease control in uninfected areas. PLoS Negl Trop Dis 2014; 8:e3120. [PMID: 25210729 PMCID: PMC4161325 DOI: 10.1371/journal.pntd.0003120] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 07/15/2014] [Indexed: 11/21/2022] Open
Abstract
Following almost 30 years of relative silence, chikungunya fever reemerged in Kenya in 2004. It subsequently spread to the islands of the Indian Ocean, reaching Southeast Asia in 2006. The virus was first detected in Cambodia in 2011 and a large outbreak occurred in the village of Trapeang Roka Kampong Speu Province in March 2012, in which 44% of the villagers had a recent infection biologically confirmed. The epidemic curve was constructed from the number of biologically-confirmed CHIKV cases per day determined from the date of fever onset, which was self-reported during a data collection campaign conducted in the village after the outbreak. All individuals participating in the campaign had infections confirmed by laboratory analysis, allowing for the identification of asymptomatic cases and those with an unreported date of fever onset. We develop a stochastic model explicitly including such cases, all of whom do not appear on the epidemic curve. We estimate the basic reproduction number of the outbreak to be 6.46 (95% C.I. [6.24, 6.78]). We show that this estimate is particularly sensitive to changes in the biting rate and mosquito longevity. Our model also indicates that the infection was more widespread within the population on the reported epidemic start date. We show that the exclusion of asymptomatic cases and cases with undocumented onset dates can lead to an underestimation of the reproduction number which, in turn, could negatively impact control strategies implemented by public health authorities. We highlight the need for properly documenting newly emerging pathogens in immunologically naive populations and the importance of identifying the route of disease introduction. During the recent resurgence of chikungunya, the scale of imported cases into previously unaffected countries has caused great concern due to the presence of a competent vector (Aedes albopictus) in many of these regions. This study describes a mathematical model for a chikungunya outbreak in the rural Cambodian village of Trapeang Roka, where a chikungunya epidemic was recorded and documented in March 2012. The outbreak data is unique, in that all infections were confirmed by laboratory analysis, enabling the identification of asymptomatic individuals, in addition to individuals who failed to report details of their infection. A stochastic model, partitioning the infectious population into three distinct classes, is implemented using Gillespie's algorithm. We show that the incorporation of both biologically-confirmed symptomatic cases undocumented by date of fever onset and asymptomatic cases yields a higher estimate of the reproduction number. Our results highlight how reproduction numbers could be underestimated by limiting analysis to the epidemic curve. Carefully documenting cases and performing laboratory testing in cluster regions, such as the village considered here, could provide a more comprehensive insight into the true infection dynamics.
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Affiliation(s)
| | - Anne Conan
- Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Veasna Duong
- Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Sowath Ly
- Institut Pasteur du Cambodge, Phnom Penh, Cambodia
| | - Chantha Ngan
- National Dengue Control Program, Ministry of Health, Phnom Penh, Cambodia
| | | | | | - Xavier Rodó
- Institut Català de Ciències del Clima, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
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