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  1. Abstract Background

    Effectively controlling heartworm disease—a major parasitic disease threatening animal health in the US and globally—requires understanding the local ecology of mosquito vectors involved in transmission. However, the key vector species in a given region are often unknown and challenging to identify. Here we investigate (i) the key vector species associated with transmission of the parasite,Dirofilaria immitis, in California and (ii) the climate and land cover drivers of vector presence.

    Methods

    To identify key mosquito vectors involved in transmission, we incorporated long-term, finely resolved mosquito surveillance data and dog heartworm case data in a statistical modeling approach (fixed-effects regression) that rigorously controls for other unobserved drivers of heartworm cases. We then used a flexible machine learning approach (gradient boosted machines) to identify the climate and land cover variables associated with the presence of each species.

    Results

    We found significant, regionally specific, positive associations between dog heartworm cases and the abundance of four vector species:Aedes aegypti(Central California),Ae. albopictus(Southern California),Ae. sierrensis(Central California), andCuliseta incidens(Northern and Central California). The proportion of developed land cover was one of the most important ecological variables predicting the presence or absence of the putative vector species.

    Conclusion

    Our results implicate three previously under-recognized vectors of dog heartworm transmission in Californiamore »and indicate the land cover types in which each putative vector species is commonly found. Efforts to target these species could prioritize surveillance in these land cover types (e.g. near human dwellings in less urbanized settings forAe. albopictusandCs. incidens) but further investigation on the natural infection prevalence and host-biting rates of these species, as well as the other local vectors, is needed.

    Graphical Abstract« less
  2. Our world is undergoing rapid planetary changes driven by human activities, often mediated by economic incentives and resource management, affecting all life on Earth. Concurrently, many infectious diseases have recently emerged or spread into new populations. Mounting evidence suggests that global change—including climate change, land-use change, urbanization, and global movement of individuals, species, and goods—may be accelerating disease emergence by reshaping ecological systems in concert with socioeconomic factors. Here, we review insights, approaches, and mechanisms by which global change drives disease emergence from a disease ecology perspective. We aim to spur more interdisciplinary collaboration with economists and identification of more effective and sustainable interventions to prevent disease emergence. While almost all infectious diseases change in response to global change, the mechanisms and directions of these effects are system specific, requiring new, integrated approaches to disease control that recognize linkages between environmental and economic sustainability and human and planetary health. Expected final online publication date for the Annual Review of Resource Economics, Volume 14 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
    Free, publicly-accessible full text available October 5, 2023
  3. ABSTRACT. Identifying the effects of environmental change on the transmission of vectorborne and zoonotic diseases is of fundamental importance in the face of rapid global change. Causal inference approaches, including instrumental variable (IV) estimation, hold promise in disentangling plausibly causal relationships from observational data in these complex systems. Valle and Zorello Laporta recently critiqued the application of such approaches in our recent study of the effects of deforestation on malaria transmission in the Brazilian Amazon on the grounds that key statistical assumptions were not met. Here, we respond to this critique by 1) deriving the IV estimator to clarify the assumptions that Valle and Zorello Laporta conflate and misrepresent in their critique, 2) discussing these key assumptions as they relate to our original study and how our original approach reasonably satisfies the assumptions, and 3) presenting model results using alternative instrumental variables that can be argued more strongly satisfy key assumptions, illustrating that our results and original conclusion—that deforestation drives malaria transmission—remain unchanged.
  4. Identifying the key vector and host species that drive the transmission of zoonotic pathogens is notoriously difficult but critical for disease control. We present a nested approach for quantifying the importance of host and vectors that integrates species’ physiological competence with their ecological traits. We apply this framework to a medically important arbovirus, Ross River virus (RRV), in Brisbane, Australia. We find that vertebrate hosts with high physiological competence are not the most important for community transmission; interactions between hosts and vectors largely underpin the importance of host species. For vectors, physiological competence is highly important. Our results identify primary and secondary vectors of RRV and suggest two potential transmission cycles in Brisbane: an enzootic cycle involving birds and an urban cycle involving humans. The framework accounts for uncertainty from each fitted statistical model in estimates of species’ contributions to transmission and has has direct application to other zoonotic pathogens.
  5. Barrera, Roberto (Ed.)
    Arboviruses transmitted by Aedes aegypti (e.g., dengue, chikungunya, Zika) are of major public health concern on the arid coastal border of Ecuador and Peru. This high transit border is a critical disease surveillance site due to human movement-associated risk of transmission. Local level studies are thus integral to capturing the dynamics and distribution of vector populations and social-ecological drivers of risk, to inform targeted public health interventions. Our study examines factors associated with household-level Ae . aegypti presence in Huaquillas, Ecuador, while accounting for spatial and temporal effects. From January to May of 2017, adult mosquitoes were collected from a cohort of households (n = 63) in clusters (n = 10), across the city of Huaquillas, using aspirator backpacks. Household surveys describing housing conditions, demographics, economics, travel, disease prevention, and city services were conducted by local enumerators. This study was conducted during the normal arbovirus transmission season (January—May), but during an exceptionally dry year. Household level Ae . aegypti presence peaked in February, and counts were highest in weeks with high temperatures and a week after increased rainfall. Univariate analyses with proportional odds logistic regression were used to explore household social-ecological variables and female Ae . aegypti presence. We foundmore »that homes were more likely to have Ae . aegypti when households had interruptions in piped water service. Ae . aegypti presence was less likely in households with septic systems. Based on our findings, infrastructure access and seasonal climate are important considerations for vector control in this city, and even in dry years, the arid environment of Huaquillas supports Ae . aegypti breeding habitat.« less
  6. When a rare pathogen emerges to cause a pandemic, it is critical to understand its dynamics and the impact of mitigation measures. We use experimental data to parametrize a temperature-dependent model of Zika virus (ZIKV) transmission dynamics and analyse the effects of temperature variability and control-related parameters on the basic reproduction number ( R 0 ) and the final epidemic size of ZIKV. Sensitivity analyses show that these two metrics are largely driven by different parameters, with the exception of temperature, which is the dominant driver of epidemic dynamics in the models. Our R 0 estimate has a single optimum temperature (≈30°C), comparable to other published results (≈29°C). However, the final epidemic size is maximized across a wider temperature range, from 24 to 36°C. The models indicate that ZIKV is highly sensitive to seasonal temperature variation. For example, although the model predicts that ZIKV transmission cannot occur at a constant temperature below 23°C (≈ average annual temperature of Rio de Janeiro, Brazil), the model predicts substantial epidemics for areas with a mean temperature of 20°C if there is seasonal variation of 10°C (≈ average annual temperature of Tampa, Florida). This suggests that the geographical range of ZIKV is wider thanmore »indicated from static R 0 models, underscoring the importance of climate dynamics and variation in the context of broader climate change on emerging infectious diseases.« less
  7. Ostling, Annette (Ed.)
  8. The potential for adaptive evolution to enable species persistence under a changing climate is one of the most important questions for understanding impacts of future climate change. Climate adaptation may be particularly likely for short-lived ectotherms, including many pest, pathogen, and vector species. For these taxa, estimating climate adaptive potential is critical for accurate predictive modeling and public health preparedness. Here, we demonstrate how a simple theoretical framework used in conservation biology—evolutionary rescue models—can be used to investigate the potential for climate adaptation in these taxa, using mosquito thermal adaptation as a focal case. Synthesizing current evidence, we find that short mosquito generation times, high population growth rates, and strong temperature-imposed selection favor thermal adaptation. However, knowledge gaps about the extent of phenotypic and genotypic variation in thermal tolerance within mosquito populations, the environmental sensitivity of selection, and the role of phenotypic plasticity constrain our ability to make more precise estimates. We describe how common garden and selection experiments can be used to fill these data gaps. Lastly, we investigate the consequences of mosquito climate adaptation on disease transmission using Aedes aegypti -transmitted dengue virus in Northern Brazil as a case study. The approach outlined here can be applied tomore »any disease vector or pest species and type of environmental change.« less