Thermal biology of mosquito‐borne disease

Mordecai, Erin A.; Caldwell, Jamie M.; Grossman, Marissa K.; Lippi, Catherine A.; Johnson, Leah R.; Neira, Marco; Rohr, Jason R.; Ryan, Sadie J.; Savage, Van M.; Shocket, Marta S.; Sippy, Rachel; Stewart-Ibarra, Anna M.; Thomas, Matthew B.; Villena, Oswaldo C.

doi:10.1111/ele.13335

Cited by 391 publications

(532 citation statements)

References 167 publications

(421 reference statements)

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“…In contrast, the modeling approach used here is mechanistic and “bottom-up,” wherein the life history of mosquitoes and pathogens, and their responses to temperature, are explicitly quantified based on empirical, laboratory-based data and incorporated into the model to predict where suitability for transmission is likely to occur. A mechanistic model, built independently of case outcome data, allows for validation with empirical, field-collected data, and obviates the bias of modeling data while intervention is ongoing, as is inevitably the case with previous approaches [30].…”

Section: Discussionmentioning

confidence: 99%

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

Ryan

Lippi

Zermoglio³

2019

Preprint

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AbstractBackgroundMalaria continues to be a disease of massive burden in Africa, and the public health resources targeted at surveillance, prevention, control, and intervention comprise large outlays of expense. Malaria transmission is largely constrained by the suitability of the climate for Anopheles mosquitoes and Plasmodium parasite development. Thus, as climate changes, we will see shifts in geographic locations suitable for transmission, and differing lengths of seasons of suitability, which will require changes in the types and amounts of resources.MethodsWe mapped the shifting geographic risk of malaria transmission, in context of changing seasonality (i.e. endemic to epidemic, and vice-versa), and the number of people affected. We applied a temperature-dependent model of malaria transmission suitability to continental gridded climate data for multiple future climate model projections. We aligned the resulting outcomes with programmatic needs to provide summaries at national and regional scales for the African continent. Model outcomes were combined with population projections to estimate the population at risk at three points in the future, 2030, 2050, and 2080, under two scenarios of greenhouse gas emissions (RCP4.5 and RCP8.5).ResultsGeographic shifts in endemic and seasonal suitability for malaria transmission were observed across all future scenarios of climate change. The worst-case regional scenario (RCP8.5) of climate change places an additional 75.9 million people at risk from endemic (10-12 months) exposure to malaria transmission in Eastern and Southern Africa by the year 2080, with the greatest population at risk in Eastern Africa. Despite a predominance of reduction in season length, a net gain of 51.3 million additional people will be put at some level of risk in Western Africa by midcentury.ConclusionsThis study provides an updated view of potential malaria geographic shifts in Africa under climate change for the more recent climate model projections (AR5), and a tool for aligning findings with programmatic needs at key scales for decision makers. In describing shifting seasonality, we can capture transitions between endemic and epidemic risk areas, to facilitate the planning for interventions aimed at year-round risk versus anticipatory surveillance and rapid response to potential outbreak locations.

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Section: Discussionmentioning

confidence: 99%

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

Ryan

Lippi

Zermoglio³

2019

Preprint

Self Cite

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“…stephensi data dramatically changed the predicted relationship between the environmental suitability of malaria transmission and temperature relative to the previously published Multi-species estimated model based largely on An. gambiae and P. falciparum (31), suggesting that the thermal limits and optima of relative R 0 (T) models varies across disease systems (26, 78). Specifically, we demonstrate a 3.4°C decrease in the predicted thermal minimum and 3.4°C increase in the thermal maximum for our An.…”

Section: Discussionmentioning

confidence: 99%

Mosquito species and age influence thermal performance of traits relevant to malaria transmission

Miazgowicz¹,

Mordecai

Ryan

et al. 2019

Preprint

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2 3 Models predicting disease transmission are a vital tool in the control of mosquito populations and 2 4 3 1 temperature-trait relationships estimated based on daily rates versus directly observed lifetime 3 2 values. Incorporating these temperature-trait relationships into an expression governing 3 3 transmission suitability, relative R 0 (T), model resulted in minor differences in the breadth of 3 4 suitable temperatures for Plasmodium falciparum transmission between the two models 3 5 constructed from only An. stephensi trait data, but a substantial increase in breadth compared to a 3 6 previously published model consisting of trait data from multiple mosquito species. Overall this 3 7 work highlights the importance of considering how mosquito trait values vary with mosquito age 3 8 and mosquito species when generating temperature-based environmental suitability predictions 3 9 of transmission. 4 0 Introduction 4 3 Despite the progress of global malaria elimination programs in reducing the incidence of 4 4 human malaria, particularly Plasmodium falciparum, malaria remains a leading cause of 4 5 morbidity and mortality among infectious diseases (1). The occurrence of multi-class drug and 4 6 insecticide resistance, in addition to alterations in mosquito behavior, challenge our ability to 4 7 eradicate malaria and poses the possibility of resurgence (1-6). While numerous environmental 4 8 factors affect the distribution and prevalence of mosquito-borne diseases, temperature is one of 4 9 7 2 temperatures in northern latitudes become more permissive and suitable seasons extend (24, 32, 7 3 49).7 4 Despite these advances, insights from previous mechanistic R 0 models remain 7 5 constrained by a lack of entomological and parasite data (31). Temperature-trait relationships for 7 6 key parameters are often indirectly estimated from a limited number of studies, leading to high 7 7uncertainty around the predicted thermal limits in current malaria R 0 models (31, 32). 8Additionally, the parameterization of R 0 models with temperature-trait relationships aggregated 7 9 from different mosquito and parasite species likely introduces error and uncertainty in R 0 8 0 estimates given the degree of inter-and intra-species variation in life history (7, 31, 32). 8 1 Further, evidence from a diversity of invertebrate systems demonstrates that organisms 8 2 experience age-related changes in life history traits (50-53). These changes reflect either 8 3 senescence, a decline in general physiological function with age, or a shift in energy allocation to 8 4 different life history tasks as an organism ages to maximize fitness. Limited studies suggest that 8 5 age modifies mosquito life history, with some evidence that mosquitoes experience reproductive 8 6 senescence (54), bite more frequently as they age (55), and exhibit age-dependent survivorship 8 7 (52). Yet, incorporating the combined effect of temperature and age on mosquito life history 8 8 traits has not been explicitly addressed in temperature-dependent R 0 models for mala...

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“…However, the relationship between virus transmission and temperature is not linear, and is characterised by optimal transmission temperatures and bounded by thresholds, below and above which transmission does not occur, and these temperature effects vary by both mosquito species and pathogen. 37 To an upper threshold, virus replication is sped up under warmer ambient temperatures, also enhancing transmission potential. Temperature effects on mosquito abundance are also moderated by humidity and rainfall.…”

Section: Australian Adaptation Plans For Healthmentioning

confidence: 99%

The 2019 report of theMJA–LancetCountdown on health and climate change: a turbulent year with mixed progress

Beggs

Zhang

Bambrick

et al. 2019

Medical Journal of Australia

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Summary The MJA–Lancet Countdown on health and climate change was established in 2017 and produced its first Australian national assessment in 2018. It examined 41 indicators across five broad domains: climate change impacts, exposures and vulnerability; adaptation, planning and resilience for health; mitigation actions and health co‐benefits; economics and finance; and public and political engagement. It found that, overall, Australia is vulnerable to the impacts of climate change on health, and that policy inaction in this regard threatens Australian lives. In this report we present the 2019 update. We track progress on health and climate change in Australia across the same five broad domains and many of the same indicators as in 2018. A number of new indicators are introduced this year, including one focused on wildfire exposure, and another on engagement in health and climate change in the corporate sector. Several of the previously reported indicators are not included this year, either due to their discontinuation by the parent project, the Lancet Countdown, or because insufficient new data were available for us to meaningfully provide an update to the indicator. In a year marked by an Australian federal election in which climate change featured prominently, we find mixed progress on health and climate change in this country. There has been progress in renewable energy generation, including substantial employment increases in this sector. There has also been some progress at state and local government level. However, there continues to be no engagement on health and climate change in the Australian federal Parliament, and Australia performs poorly across many of the indicators in comparison to other developed countries; for example, it is one of the world's largest net exporters of coal and its electricity generation from low carbon sources is low. We also find significantly increasing exposure of Australians to heatwaves and, in most states and territories, continuing elevated suicide rates at higher temperatures. We conclude that Australia remains at significant risk of declines in health due to climate change, and that substantial and sustained national action is urgently required in order to prevent this.

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Thermal biology of mosquito‐borne disease

Cited by 391 publications

References 167 publications

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention

Mosquito species and age influence thermal performance of traits relevant to malaria transmission

The 2019 report of theMJA–LancetCountdown on health and climate change: a turbulent year with mixed progress

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