scholarly journals Local adaptation of a parasite to solar radiation impacts disease transmission potential, spore yield, and host fecundity*

Evolution ◽  
2020 ◽  
Vol 74 (8) ◽  
pp. 1856-1864 ◽  
Author(s):  
Mary Alta Rogalski ◽  
Meghan A. Duffy
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Divine Ekwem ◽  
Thomas A. Morrison ◽  
Richard Reeve ◽  
Jessica Enright ◽  
Joram Buza ◽  
...  

AbstractIn Africa, livestock are important to local and national economies, but their productivity is constrained by infectious diseases. Comprehensive information on livestock movements and contacts is required to devise appropriate disease control strategies; yet, understanding contact risk in systems where herds mix extensively, and where different pathogens can be transmitted at different spatial and temporal scales, remains a major challenge. We deployed Global Positioning System collars on cattle in 52 herds in a traditional agropastoral system in western Serengeti, Tanzania, to understand fine-scale movements and between-herd contacts, and to identify locations of greatest interaction between herds. We examined contact across spatiotemporal scales relevant to different disease transmission scenarios. Daily cattle movements increased with herd size and rainfall. Generally, contact between herds was greatest away from households, during periods with low rainfall and in locations close to dipping points. We demonstrate how movements and contacts affect the risk of disease spread. For example, transmission risk is relatively sensitive to the survival time of different pathogens in the environment, and less sensitive to transmission distance, at least over the range of the spatiotemporal definitions of contacts that we explored. We identify times and locations of greatest disease transmission potential and that could be targeted through tailored control strategies.


2021 ◽  
Author(s):  
Divine Ekwem ◽  
Thomas A. Morrison ◽  
Richard Reeve ◽  
Jessica Enright ◽  
Joram Buza ◽  
...  

Abstract In Africa, livestock are important to local and national economies, but their productivity is constrained by infectious diseases. Comprehensive information on livestock movements and contacts is required to devise appropriate disease control strategies; yet, understanding contact risk in systems where herds mix extensively, and where different pathogens can be transmitted at different spatial and temporal scales, remains a major challenge. We deployed Global Positioning System collars on cattle in 52 herds in a traditional agropastoral system in western Serengeti, Tanzania, to understand fine-scale movements and between-herd contacts, and to identify locations of greatest interaction between herds. We examined contact across spatiotemporal scales relevant to different disease transmission scenarios. Daily cattle movements increased with herd size and rainfall. Generally, contact was greatest away from households, during periods with low rainfall and in locations close to dipping points. We demonstrate how movements and contacts affect the risk of disease spread. For example, contact rate was relatively sensitive to the survival time of different pathogens in the environment, and less sensitive to transmission distance, at least over the range of values that we explored. We identify times and locations of greatest disease transmission potential and that could be targeted through tailored control strategies.


2020 ◽  
Vol 12 (1) ◽  
pp. 120-127
Author(s):  
Vinod Baniya ◽  
Ram Keval

Mathematical modeling of Japanese encephalitis (JE) disease in human population with pig and mosquito has been presented in this paper. The proposed model, which involves three compartments of human (Susceptible, Vaccinated, Infected), two compartments of mosquito (Susceptible, Infected) and three compartments of the pig (Susceptible, Vaccinated, Infected). In this work, it is assumed that JE spreads between susceptible class and infected mosquitoes only. Basic results like boundedness of the model, the existence of equilibrium and local stability issues are investigated. Here, to measure the disease transmission potential in the population the basic reproduction number (R0) from the system has been analyzed w.r.t. control parameters both numerically and theoretically. The dynamical behaviors of the system have been analyzed by using the stability theory of differential equations and numerical simulations at equilibrium points. A numerical verification of results is carried out of the model under consideration.


2015 ◽  
Vol 143 (16) ◽  
pp. 3359-3374 ◽  
Author(s):  
W. D. TANNER ◽  
D. J. A. TOTH ◽  
A. V. GUNDLAPALLI

SummaryIn March 2013 the first cases of human avian influenza A(H7N9) were reported to the World Health Organization. Since that time, over 650 cases have been reported. Infections are associated with considerable morbidity and mortality, particularly within certain demographic groups. This rapid increase in cases over a brief time period is alarming and has raised concerns about the pandemic potential of the H7N9 virus. Three major factors influence the pandemic potential of an influenza virus: (1) its ability to cause human disease, (2) the immunity of the population to the virus, and (3) the transmission potential of the virus. This paper reviews what is currently known about each of these factors with respect to avian influenza A(H7N9). Currently, sustained human-to-human transmission of H7N9 has not been reported; however, population immunity to the virus is considered very low, and the virus has significant ability to cause human disease. Several statistical and geographical modelling studies have estimated and predicted the spread of the H7N9 virus in humans and avian species, and some have identified potential risk factors associated with disease transmission. Additionally, assessment tools have been developed to evaluate the pandemic potential of H7N9 and other influenza viruses. These tools could also hypothetically be used to monitor changes in the pandemic potential of a particular virus over time.


2017 ◽  
Vol 14 (128) ◽  
pp. 20160481 ◽  
Author(s):  
Samuel P. C. Brand ◽  
Matt J. Keeling

It is a long recognized fact that climatic variations, especially temperature, affect the life history of biting insects. This is particularly important when considering vector-borne diseases, especially in temperate regions where climatic fluctuations are large. In general, it has been found that most biological processes occur at a faster rate at higher temperatures, although not all processes change in the same manner. This differential response to temperature, often considered as a trade-off between onward transmission and vector life expectancy, leads to the total transmission potential of an infected vector being maximized at intermediate temperatures. Here we go beyond the concept of a static optimal temperature, and mathematically model how realistic temperature variation impacts transmission dynamics. We use bluetongue virus (BTV), under UK temperatures and transmitted by Culicoides midges, as a well-studied example where temperature fluctuations play a major role. We first consider an optimal temperature profile that maximizes transmission, and show that this is characterized by a warm day to maximize biting followed by cooler weather to maximize vector life expectancy. This understanding can then be related to recorded representative temperature patterns for England, the UK region which has experienced BTV cases, allowing us to infer historical transmissibility of BTV, as well as using forecasts of climate change to predict future transmissibility. Our results show that when BTV first invaded northern Europe in 2006 the cumulative transmission intensity was higher than any point in the last 50 years, although with climate change such high risks are the expected norm by 2050. Such predictions would indicate that regular BTV epizootics should be expected in the UK in the future.


2013 ◽  
Vol 280 (1769) ◽  
pp. 20131500 ◽  
Author(s):  
J. Randall ◽  
J. Cable ◽  
I. A. Guschina ◽  
J. L. Harwood ◽  
J. Lello

Endemic, low-virulence parasitic infections are common in nature. Such infections may deplete host resources, which in turn could affect the reproduction of other parasites during co-infection. We aimed to determine whether the reproduction, and therefore transmission potential, of an epidemic parasite was limited by energy costs imposed on the host by an endemic infection. Total lipids, triacylglycerols (TAG) and polar lipids were measured in cockroaches ( Blattella germanica ) that were fed ad libitum, starved or infected with an endemic parasite, Gregarina blattarum. Reproductive output of an epidemic parasite, Steinernema carpocapsae , was then assessed by counting the number of infective stages emerging from these three host groups. We found both starvation and gregarine infection reduced cockroach lipids, mainly through depletion of TAG. Further, both starvation and G. blattarum infection resulted in reduced emergence of nematode transmission stages. This is, to our knowledge, the first study to demonstrate directly that host resource depletion caused by endemic infection could affect epidemic disease transmission. In view of the ubiquity of endemic infections in nature, future studies of epidemic transmission should take greater account of endemic co-infections.


2021 ◽  
Vol 17 (1) ◽  
pp. e1009196
Author(s):  
Jonathon A. Siva-Jothy ◽  
Pedro F. Vale

Host heterogeneity in disease transmission is widespread but precisely how different host traits drive this heterogeneity remains poorly understood. Part of the difficulty in linking individual variation to population-scale outcomes is that individual hosts can differ on multiple behavioral, physiological and immunological axes, which will together impact their transmission potential. Moreover, we lack well-characterized, empirical systems that enable the quantification of individual variation in key host traits, while also characterizing genetic or sex-based sources of such variation. Here we used Drosophila melanogaster and Drosophila C Virus as a host-pathogen model system to dissect the genetic and sex-specific sources of variation in multiple host traits that are central to pathogen transmission. Our findings show complex interactions between genetic background, sex, and female mating status accounting for a substantial proportion of variance in lifespan following infection, viral load, virus shedding, and viral load at death. Two notable findings include the interaction between genetic background and sex accounting for nearly 20% of the variance in viral load, and genetic background alone accounting for ~10% of the variance in viral shedding and in lifespan following infection. To understand how variation in these traits could generate heterogeneity in individual pathogen transmission potential, we combined measures of lifespan following infection, virus shedding, and previously published data on fly social aggregation. We found that the interaction between genetic background and sex explained ~12% of the variance in individual transmission potential. Our results highlight the importance of characterising the sources of variation in multiple host traits to understand the drivers of heterogeneity in disease transmission.


2021 ◽  
Vol 2 ◽  
Author(s):  
Lorena M. Simon ◽  
Thiago F. Rangel

Dengue is an ongoing problem, especially in tropical countries. Like many other vector-borne diseases, the spread of dengue is driven by a myriad of climate and socioeconomic factors. Within developing countries, heterogeneities on socioeconomic factors are expected to create variable conditions for dengue transmission. However, the relative role of socioeconomic characteristics and their association with climate in determining dengue prevalence are poorly understood. Here we assembled essential socioeconomic factors over 5570 municipalities across Brazil and assessed their effect on dengue prevalence jointly with a previously predicted temperature suitability for transmission. Using a simultaneous autoregressive approach (SAR), we showed that the variability in the prevalence of dengue cases across Brazil is primarily explained by the combined effect of climate and socioeconomic factors. At some dengue seasons, the effect of temperature on transmission potential showed to be a more significant proxy of dengue cases. Still, socioeconomic factors explained the later increase in dengue prevalence over Brazil. In a heterogeneous country such as Brazil, recognizing the transmission drivers by vectors is a fundamental issue in effectively predicting and combating tropical diseases like dengue. Ultimately, it indicates that not considering socioeconomic factors in disease transmission predictions might compromise efficient surveillance strategies. Our study shows that sanitation, urbanization, and GDP are regional indicators that should be considered along with temperature suitability on dengue transmission, setting effective directions to mosquito-borne disease control.


2022 ◽  
Vol 19 (186) ◽  
Author(s):  
Kayla Kauffman ◽  
Courtney S. Werner ◽  
Georgia Titcomb ◽  
Michelle Pender ◽  
Jean Yves Rabezara ◽  
...  

Social and spatial network analysis is an important approach for investigating infectious disease transmission, especially for pathogens transmitted directly between individuals or via environmental reservoirs. Given the diversity of ways to construct networks, however, it remains unclear how well networks constructed from different data types effectively capture transmission potential. We used empirical networks from a population in rural Madagascar to compare social network survey and spatial data-based networks of the same individuals. Close contact and environmental pathogen transmission pathways were modelled with the spatial data. We found that naming social partners during the surveys predicted higher close-contact rates and the proportion of environmental overlap on the spatial data-based networks. The spatial networks captured many strong and weak connections that were missed using social network surveys alone. Across networks, we found weak correlations among centrality measures (a proxy for superspreading potential). We conclude that social network surveys provide important scaffolding for understanding disease transmission pathways but miss contact-specific heterogeneities revealed by spatial data. Our analyses also highlight that the superspreading potential of individuals may vary across transmission modes. We provide detailed methods to construct networks for close-contact transmission pathogens when not all individuals simultaneously wear GPS trackers.


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