Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0002
R. C. Reiner, David L. Smith
A theory for the transmission dynamics and control of malaria was developed around a set of concepts, quantities, and mathematical models introduced by Ronald Ross. Decades later, Macdonald linked Ross's models to epidemiological and entomological data, developed the concept of the basic reproductive number, R0, and proposed a rudimentary theory of control based on sensitivity to parameters. Here, we review development of the Ross–Macdonald model, present one simple version, and provide an eclectic critique of the theory based on studies conducted more recently. While mosquito populations are logically necessary for mosquito-borne pathogen transmission, the study of transmission since then shows it is noisy, heterogeneous, and complex. Heterogeneity, stochasticity, and complexity represent important challenges for applying theory in context.
{"title":"Heterogeneity, Stochasticity and Complexity in the Dynamics and Control of Mosquito-Borne Pathogens","authors":"R. C. Reiner, David L. Smith","doi":"10.1093/OSO/9780198853244.003.0002","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0002","url":null,"abstract":"A theory for the transmission dynamics and control of malaria was developed around a set of concepts, quantities, and mathematical models introduced by Ronald Ross. Decades later, Macdonald linked Ross's models to epidemiological and entomological data, developed the concept of the basic reproductive number, R0, and proposed a rudimentary theory of control based on sensitivity to parameters. Here, we review development of the Ross–Macdonald model, present one simple version, and provide an eclectic critique of the theory based on studies conducted more recently. While mosquito populations are logically necessary for mosquito-borne pathogen transmission, the study of transmission since then shows it is noisy, heterogeneous, and complex. Heterogeneity, stochasticity, and complexity represent important challenges for applying theory in context.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"122 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126146123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0008
M. Diuk-Wasser, Maria P Fernandez, S. Davis
Tick-borne pathogens pose the greatest vector-borne disease burden in temperate areas of Europe and North America. We synthesize key aspects of tick life history that enable ticks to persist, spread and impact human health, including a two-year life cycle, multiple transmission pathways and dependence on hosts for tick feeding, movement and pathogen transmission. We discuss modeling advances that incorporate these traits in the context of climate-driven variation in tick feeding phenology. For established pathogens, such as the Lyme disease agent in the United States, we disentangle the linkages between land use change, habitat fragmentation and host diversity influencing human risk of infection along an urbanization gradient. We propose a coupled natural-human system framework for tick-borne pathogens that accounts for nonlinear effects and feedbacks between the enzootic cycle and human spillover. A deeper understanding of the eco-bio-social determinants of these diseases is required to develop more effective public health interventions.
{"title":"Ecological Interactions Influencing the Emergence, Abundance, and Human Exposure to Tick-Borne Pathogens","authors":"M. Diuk-Wasser, Maria P Fernandez, S. Davis","doi":"10.1093/OSO/9780198853244.003.0008","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0008","url":null,"abstract":"Tick-borne pathogens pose the greatest vector-borne disease burden in temperate areas of Europe and North America. We synthesize key aspects of tick life history that enable ticks to persist, spread and impact human health, including a two-year life cycle, multiple transmission pathways and dependence on hosts for tick feeding, movement and pathogen transmission. We discuss modeling advances that incorporate these traits in the context of climate-driven variation in tick feeding phenology. For established pathogens, such as the Lyme disease agent in the United States, we disentangle the linkages between land use change, habitat fragmentation and host diversity influencing human risk of infection along an urbanization gradient. We propose a coupled natural-human system framework for tick-borne pathogens that accounts for nonlinear effects and feedbacks between the enzootic cycle and human spillover. A deeper understanding of the eco-bio-social determinants of these diseases is required to develop more effective public health interventions.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130424649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0009
M. Evans, Philip M. Newberry, C. Murdock
Mosquito-borne disease transmission is highly dependent on environmental conditions throughout the lifetime of a mosquito. In addition to direct effects of the current environment, carry-over effects from the environments of previous life-stages can influence an adult mosquito's life history traits. In this chapter, we review past work on the carry-over effects of temperature, nutrition, competition, and microbial diversity of the larval environment on disease transmission in mosquitoes. We then discuss how carry-over effects can be integrated into modeling studies and future directions for work on carry-over effects in mosquito-borne disease systems.
{"title":"Carry-over Effects of the Larval Environment in Mosquito-Borne Disease Systems","authors":"M. Evans, Philip M. Newberry, C. Murdock","doi":"10.1093/OSO/9780198853244.003.0009","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0009","url":null,"abstract":"Mosquito-borne disease transmission is highly dependent on environmental conditions throughout the lifetime of a mosquito. In addition to direct effects of the current environment, carry-over effects from the environments of previous life-stages can influence an adult mosquito's life history traits. In this chapter, we review past work on the carry-over effects of temperature, nutrition, competition, and microbial diversity of the larval environment on disease transmission in mosquitoes. We then discuss how carry-over effects can be integrated into modeling studies and future directions for work on carry-over effects in mosquito-borne disease systems.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126611281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0003
T. Perkins, G. España, S. Moore, R. Oidtman, Swarnali Sharma, Brajendra K. Singh, A. Siraj, K. Soda, Morgan E. Smith, M. Walters, E. Michael
Prediction of spatial heterogeneity in disease incidence based on measurable spatial factors is a major goal of spatial epidemiology. There are a number of applied goals of these predictions, including appropriately targeting resources for surveillance and intervention and accurately quantifying disease burden. Although spatial heterogeneity is evident in the epidemiology of many diseases, several aspects of the biology of vector-borne diseases amplify this form of heterogeneity. Here, we review several aspects of this biology, highlighting seven distinct ways in which the biology of vector-borne diseases impacts understanding spatial heterogeneity in disease incidence. Whereas traditional methods place emphasis on spatial regression and other forms of statistical analysis of empirical data, the goal here is to offer a perspective on potential pitfalls of analyses that take data at face value and do not acknowledge the complex, nonlinear, and dynamic relationships between spatial patterns of disease incidence and spatial heterogeneity in transmission.
{"title":"Seven Challenges for Spatial Analyses of Vector-Borne Diseases","authors":"T. Perkins, G. España, S. Moore, R. Oidtman, Swarnali Sharma, Brajendra K. Singh, A. Siraj, K. Soda, Morgan E. Smith, M. Walters, E. Michael","doi":"10.1093/OSO/9780198853244.003.0003","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0003","url":null,"abstract":"Prediction of spatial heterogeneity in disease incidence based on measurable spatial factors is a major goal of spatial epidemiology. There are a number of applied goals of these predictions, including appropriately targeting resources for surveillance and intervention and accurately quantifying disease burden. Although spatial heterogeneity is evident in the epidemiology of many diseases, several aspects of the biology of vector-borne diseases amplify this form of heterogeneity. Here, we review several aspects of this biology, highlighting seven distinct ways in which the biology of vector-borne diseases impacts understanding spatial heterogeneity in disease incidence. Whereas traditional methods place emphasis on spatial regression and other forms of statistical analysis of empirical data, the goal here is to offer a perspective on potential pitfalls of analyses that take data at face value and do not acknowledge the complex, nonlinear, and dynamic relationships between spatial patterns of disease incidence and spatial heterogeneity in transmission.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133708244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0005
J. Drake, K. Magori, Kevin Knoblich, Sarah Bowden, W. Bajwa
The size of annual outbreaks in seasonally forced host-pathogen systems is poorly understood. We studied contributing factors to the six-fold observed variation in the number of human cases of West Nile virus in New York City in the years 2000–2008. Sampling error and intrinsic noise (demographic stochasticity) explain roughly half of the observed variation. To investigate the remaining sources of variation, we estimated the monthly force of infection from data on the distribution and abundance of mosquitoes, virus prevalence, vector competence, and mammal biting rate at two spatial scales. At both scales, the West Nile virus force of infection was remarkably consistent from year to year. We propose that fine scale spatial heterogeneity is the key to understanding the epidemiology of West Nile virus in New York City.
{"title":"Force of Infection and Variation in Outbreak Size in a Multi-Species Host-Pathogen System","authors":"J. Drake, K. Magori, Kevin Knoblich, Sarah Bowden, W. Bajwa","doi":"10.1093/OSO/9780198853244.003.0005","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0005","url":null,"abstract":"The size of annual outbreaks in seasonally forced host-pathogen systems is poorly understood. We studied contributing factors to the six-fold observed variation in the number of human cases of West Nile virus in New York City in the years 2000–2008. Sampling error and intrinsic noise (demographic stochasticity) explain roughly half of the observed variation. To investigate the remaining sources of variation, we estimated the monthly force of infection from data on the distribution and abundance of mosquitoes, virus prevalence, vector competence, and mammal biting rate at two spatial scales. At both scales, the West Nile virus force of infection was remarkably consistent from year to year. We propose that fine scale spatial heterogeneity is the key to understanding the epidemiology of West Nile virus in New York City.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125581262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0012
M. Levy
The forces that lead to the emergence of Trypanosoma cruzi, the etiologic agent of Chagas disease, are often distinct from those that maintain its transmission, and these are distinct again from those that allow the parasite to persist over decades. Just as kindling, logs, and coals all play discrete roles in the growth of a fire, a myriad of mammalian hosts contribute differently to epidemics of Trypanosoma. cruzi. Chagas disease affects millions of people in the Americas, and, through migration, thousands more on other continents. The agent of the disease, Trypanosoma cruzi, is a slender, highly-motile, unicellular parasite. T. cruzi does not migrate to the salivary glands of its insect vector–the blood-sucking triatomine insects–as many other vector-borne parasites do.
{"title":"Kindling, Logs, and Coals: The Dynamics of Trypanosoma cruzi, the Etiological Agent of Chagas Disease in Arequipa, Peru","authors":"M. Levy","doi":"10.1093/OSO/9780198853244.003.0012","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0012","url":null,"abstract":"The forces that lead to the emergence of Trypanosoma cruzi, the etiologic agent of Chagas disease, are often distinct from those that maintain its transmission, and these are distinct again from those that allow the parasite to persist over decades. Just as kindling, logs, and coals all play discrete roles in the growth of a fire, a myriad of mammalian hosts contribute differently to epidemics of Trypanosoma. cruzi. Chagas disease affects millions of people in the Americas, and, through migration, thousands more on other continents. The agent of the disease, Trypanosoma cruzi, is a slender, highly-motile, unicellular parasite. T. cruzi does not migrate to the salivary glands of its insect vector–the blood-sucking triatomine insects–as many other vector-borne parasites do.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115981945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1093/OSO/9780198853244.003.0011
C. Reitmayer, M. Evans, Kerri L. Miazgowicz, Philip M. Newberry, N. Solano, Blanka Tesla, C. Murdock
Vector-borne viruses (arboviruses) are emerging threats to both human and animal health. The global expansion of dengue virus, West Nile virus, chikungunya, and most recently Zika virus are prominent examples of how quickly mosquito-transmitted viruses can emerge and spread. We currently lack high quality data from a diversity of mosquito-arbovirus systems on the specific mosquito and viral traits that drive disease transmission. Further, the factors that contribute to variation in these traits and disease transmission remain largely unidentified. In this chapter, we outline and explore the following: 1. the specific mechanisms governing the outcome of vector-virus interactions 2. how genetic variation across mosquito populations and viral strains, as well as environmental variation in abiotic and biotic factors shape the mosquito-virus interaction and 3. the implications of these interactions for understanding and predicting arbovirus transmission, as well as for control of mosquito species that transmit human pathogens.
{"title":"Mosquito—Virus Interactions","authors":"C. Reitmayer, M. Evans, Kerri L. Miazgowicz, Philip M. Newberry, N. Solano, Blanka Tesla, C. Murdock","doi":"10.1093/OSO/9780198853244.003.0011","DOIUrl":"https://doi.org/10.1093/OSO/9780198853244.003.0011","url":null,"abstract":"Vector-borne viruses (arboviruses) are emerging threats to both human and animal health. The global expansion of dengue virus, West Nile virus, chikungunya, and most recently Zika virus are prominent examples of how quickly mosquito-transmitted viruses can emerge and spread. We currently lack high quality data from a diversity of mosquito-arbovirus systems on the specific mosquito and viral traits that drive disease transmission. Further, the factors that contribute to variation in these traits and disease transmission remain largely unidentified. In this chapter, we outline and explore the following: 1. the specific mechanisms governing the outcome of vector-virus interactions 2. how genetic variation across mosquito populations and viral strains, as well as environmental variation in abiotic and biotic factors shape the mosquito-virus interaction and 3. the implications of these interactions for understanding and predicting arbovirus transmission, as well as for control of mosquito species that transmit human pathogens.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130343011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-29DOI: 10.1093/oso/9780198853244.003.0004
S. Lauer, Alexandria C. Brown, N. Reich
Forecasting transmission of infectious diseases, especially for vector-borne diseases, poses unique challenges for researchers. Behaviors of and interactions between viruses, vectors, hosts, and the environment each play a part in determining the transmission of a disease. Public health surveillance systems and other sources provide valuable data that can be used to accurately forecast disease incidence. However, many aspects of common infectious disease surveillance data are imperfect: cases may be reported with a delay or in some cases not at all, data on vectors may not be available, and case data may not be available at high geographical or temporal resolution. In the face of these challenges, researchers must make assumptions to either account for these underlying processes in a mechanistic model or to justify their exclusion altogether in a statistical model.
{"title":"Infectious Disease Forecasting for Public Health","authors":"S. Lauer, Alexandria C. Brown, N. Reich","doi":"10.1093/oso/9780198853244.003.0004","DOIUrl":"https://doi.org/10.1093/oso/9780198853244.003.0004","url":null,"abstract":"Forecasting transmission of infectious diseases, especially for vector-borne diseases, poses unique challenges for researchers. Behaviors of and interactions between viruses, vectors, hosts, and the environment each play a part in determining the transmission of a disease. Public health surveillance systems and other sources provide valuable data that can be used to accurately forecast disease incidence. However, many aspects of common infectious disease surveillance data are imperfect: cases may be reported with a delay or in some cases not at all, data on vectors may not be available, and case data may not be available at high geographical or temporal resolution. In the face of these challenges, researchers must make assumptions to either account for these underlying processes in a mechanistic model or to justify their exclusion altogether in a statistical model.","PeriodicalId":416270,"journal":{"name":"Population Biology of Vector-Borne Diseases","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124124869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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