We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics.Specifically,we consider a Ross-Macdonald-type disease model on n spatial locations that are cou...We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics.Specifically,we consider a Ross-Macdonald-type disease model on n spatial locations that are coupled by host movement on a strongly connected,weighted,directed graph.We derive a closed form approximation to the domain reproduction number using a Laurent series expansion,and use this approximation to compute sensitivities of the basic reproduction number to model parameters.To illustrate how these results can be used to help inform mitigation strategies,as a case study we apply these results to malaria dynamics in Namibia,using published cell phone data and estimates for local disease transmission.Our analytical results are particularly useful for understanding drivers of transmission when mobility sinks and transmission hot spots do not coincide.展开更多
Superspreaders(individuals with a high propensity for disease spread)have played a pivotal role in recent emerging and re-emerging diseases.In disease outbreak studies,host heterogeneity based on demographic(e.g.age,s...Superspreaders(individuals with a high propensity for disease spread)have played a pivotal role in recent emerging and re-emerging diseases.In disease outbreak studies,host heterogeneity based on demographic(e.g.age,sex,vaccination status)and environmental(e.g.climate,urban/rural residence,clinics)factors are critical for the spread of infectious diseases,such as Ebola and Middle East Respiratory Syndrome(MERS).Transmission rates can vary as demographic and environmental factors are altered naturally or due to modified behaviors in response to the implementation of public health strategies.In this work,we develop stochastic models to explore the effects of demographic and environmental variability on human-to-human disease transmission rates among superspreaders in the case of Ebola and MERS.We show that the addition of environmental variability results in reduced probability of outbreak occurrence,however the severity of outbreaks that do occur increases.These observations have implications for public health strategies that aim to control environmental variables.展开更多
基金support of the Mathematical Biosciences Institute-DMS 1440386,NSF grant-DMS 1814737.
文摘We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics.Specifically,we consider a Ross-Macdonald-type disease model on n spatial locations that are coupled by host movement on a strongly connected,weighted,directed graph.We derive a closed form approximation to the domain reproduction number using a Laurent series expansion,and use this approximation to compute sensitivities of the basic reproduction number to model parameters.To illustrate how these results can be used to help inform mitigation strategies,as a case study we apply these results to malaria dynamics in Namibia,using published cell phone data and estimates for local disease transmission.Our analytical results are particularly useful for understanding drivers of transmission when mobility sinks and transmission hot spots do not coincide.
基金The authors acknowledge the support of an American Institute of Mathematics SQuaREs grantA.P.was supported by NSF grant DMS-1815750N.S.was supported by a Natural Sciences and Engineering Research Council of Canada(NSERC)Post-doctoral Fellowship.
文摘Superspreaders(individuals with a high propensity for disease spread)have played a pivotal role in recent emerging and re-emerging diseases.In disease outbreak studies,host heterogeneity based on demographic(e.g.age,sex,vaccination status)and environmental(e.g.climate,urban/rural residence,clinics)factors are critical for the spread of infectious diseases,such as Ebola and Middle East Respiratory Syndrome(MERS).Transmission rates can vary as demographic and environmental factors are altered naturally or due to modified behaviors in response to the implementation of public health strategies.In this work,we develop stochastic models to explore the effects of demographic and environmental variability on human-to-human disease transmission rates among superspreaders in the case of Ebola and MERS.We show that the addition of environmental variability results in reduced probability of outbreak occurrence,however the severity of outbreaks that do occur increases.These observations have implications for public health strategies that aim to control environmental variables.
