Agriculture has been implicated as a potential driver of human infectious diseases. However, the generality of disease-agriculture relationships has not been systematically assessed, hindering efforts to incorporate human health considerations into land-use and development policies. Here we perform a meta-analysis with 34 eligible studies and show that people who live or work in agricultural land in Southeast Asia are on average 1.74 (CI 1.47–2.07) times as likely to be infected with a pathogen than those unexposed. Effect sizes are greatest for exposure to oil palm, rubber, and non-poultry based livestock farming and for hookworm (OR 2.42, CI 1.56–3.75), malaria (OR 2.00, CI 1.46–2.73), scrub typhus (OR 2.37, CI 1.41–3.96) and spotted fever group diseases (OR 3.91, CI 2.61–5.85). In contrast, no change in infection risk is detected for faecal-oral route diseases. Although responses vary by land-use and disease types, results suggest that agricultural land-uses exacerbate many infectious diseases in Southeast Asia.

Laboratory-derived temperature dependencies of life-history traits are increasingly being used to make mechanistic predictions for how climatic warming will affect vector-borne disease dynamics, partially by affecting abundance dynamics of the vector population. These temperature–trait relationships are typically estimated from juvenile populations reared on optimal resource supply, even though natural populations of vectors are expected to experience variation in resource supply, including intermittent resource limitation. Using laboratory experiments on the mosquito Aedes aegypti , a principal arbovirus vector, combined with stage-structured population modelling, we show that low-resource supply in the juvenile life stages significantly depresses the vector's maximal population growth rate across the entire temperature range (22–32°C) and causes it to peak at a lower temperature than at high-resource supply. This effect is primarily driven by an increase in juvenile mortality and development time, combined with a decrease in adult size with temperature at low-resource supply. Our study suggests that most projections of temperature-dependent vector abundance and disease transmission are likely to be biased because they are based on traits measured under optimal resource supply. Our results provide compelling evidence for future studies to consider resource supply when predicting the effects of climate and habitat change on vector-borne disease transmission, disease vectors and other arthropods.

Mathematical models that incorporate the temperature dependence of lab-measured life history traits are increasingly being used to predict how climatic warming will affect ectotherms, including disease vectors and other arthropods. These temperature-trait relationships are typically measured under laboratory conditions that ignore how conspecific competition in depleting resource environments—a commonly occurring scenario in nature—regulates natural populations. Here, we used laboratory experiments on the mosquito Aedes aegypti, combined with a stage-structured population model, to investigate this issue. We find that intensified larval competition in ecologically-realistic depleting resource environments can significantly diminish the vector’s maximal population-level fitness across the entire temperature range, cause a ~6 °C decrease in the optimal temperature for fitness, and contract its thermal niche width by ~10 °C. Our results provide evidence for the importance of considering intra-specific competition under depleting resources when predicting how arthropod populations will respond to climatic warming.

The degree to which arthropod populations will be able to adapt to climatic warming is uncertain. Here, we report that arthropod thermal adaptation is likely to be constrained in two fundamental ways. First, maximization of population fitness with warming is predicted to be determined predominantly by the temperature of peak performance of juvenile development rate, followed by that of adult fecundity, juvenile mortality and adult mortality rates, in this specific order. Second, the differences among the temperature of peak performance of these four traits will constrain adaptation. By compiling a new global dataset of 61 diverse arthropod species, we show that contemporary populations have indeed evolved under these constraints. Our results provide a basis for using relatively feasible trait measurements to predict the adaptive capacity of arthropod populations to climatic warming.

Laboratory-derived temperature-dependencies of life history traits are increasingly being used to make mechanistic predictions for how climatic warming will affect the abundance of disease vectors. These laboratory data are typically from populations reared on optimal resource supply, even though natural populations are expected to experience fluctuations in resource availability.Using laboratory experiments and stage-structured population projection modelling, here we ask how resource limitation affects temperature-dependence of life history traits and emergent fitness of a principal arbovirus vector, Aedes aegypti, across a temperature range it typically experiences (22–32°C).We show that low-resource supply significantly depresses the vector’s maximal population growth rate (rmax) across the entire temperature range and causes it to peak at a lower temperature, than under high-resource supply. This difference is driven by the fact that resource limitation significantly increases juvenile mortality, slows development, and reduces lifespan and size at maturity (which then decreases fecundity in adults). These results show that resource supply can significantly affect the temperature-dependence of population-level fitness of disease vectors by modifying the thermal responses of underlying traits.Our study suggests that by ignoring resource limitation, projections of vector abundance and disease transmission based on laboratory studies are likely to substantially underestimate the effect of temperature on development time and juvenile survival, and overestimate the effect of temperature on lifespan, size and fecundity.Our results provide compelling evidence for future studies to consider resource supply when making predictions about the effects of climate and habitat change on disease vectors. More generally, our results point at the need to consider the effects of resource limitation on temperature-dependence of life history traits to further advance Ecological Metabolic Theory and improve its utility for predicting the responses of holometabolous insects to climate change.

Background Agricultural land use and land-use change activities are a major contributor to biodiversity loss, pollution, and carbon emissions. Evidence from multiple studies also implicates agricultural activities as a factor underlying a range of human infectious disease risks. However, these links have not been systematically assessed or quantified, hindering efforts to incorporate human health effects into land-use decision and policy making. In this study, we test and quantify the association between exposure to agricultural land use and human infectious disease risks, focusing on the highly diverse yet tractable example of southeast Asia. MethodsWe systematically reviewed English peer-reviewed publications from PubMed, EMBASE, Medline, Global Health, Google Scholar, and Web of Science databases between April 24, and Sept 10, 2017. Only studies done in southeast Asia testing the association between land use or changes in land use and infectious disease prevalence or incidence in human beings were included. We extracted crude and adjusted odds ratios (ORs) from the original studies, and for studies that did not present ORs, we calculated crude ORs provided sufficient data were available. We did a meta-analysis with mutually exclusive estimates using a random effects logistic regression model, with heterogeneity of effects addressed using prespecified subgroup analysis, the I² test for heterogeneity and the Cochrane Q test. We assessed publication bias using funnel plots, a linear regression test, and the trim and fill method, and explored the effect of potential unmeasured confounders with an E-value analysis. The primary outcome was risk of infection in people who worked in agriculture or lived in an agricultural setting.Findings Of 15 476 unique citations generated from our literature search, 37 articles were included in our metaanalysis. Our results showed that people who live or work in or near agricultural land are more likely to be infected with a pathogen than controls (OR 1•54, 95% CI 1•30-1•83, p<0•0001, E=2•16). Significant between-study heterogeneity was found, thereby warranting the use of subgroup analysis (land-use types and disease categories). No evidence of significant publication or measured or unmeasured confounder bias was detected.Interpretation The results suggest that agricultural land use consistently exacerbates human infectious disease risks in southeast Asia, highlighting a clear need to consider human health effects of agricultural land use and land-use change policies alongside effects and benefits in other sectors. Although responses clearly vary by land-use and disease types, generalisable results from this and further studies could help identify co-management opportunities for health and the environment.Funding HS has received funding from the Grantham Institute and Commonwealth Scientific and Industrial Research Organisation (CSIRO). PH has received funding from the Natural Environment Research Council.

Laboratory-derived temperature dependencies of life history traits are increasingly being used to make mechanistic predictions for how climatic warming will affect vector-borne disease dynamics, partially by affecting abundance dynamics of the vector population. These temperature-trait relationships are typically estimated from juvenile populations reared on optimal resource supply, even though natural populations of vectors are expected to experience variation in resource supply, including intermittent resource limitation. Using laboratory experiments on the mosquito Aedes aegypti, a principal arbovirus vector, combined with stage-structured population modelling, we show that low-resource supply in the juvenile life stages significantly depresses the vector's maximal population growth rate across the entire temperature range (22-32°C) and causes it to peak at a lower temperature than at high-resource supply. This effect is primarily driven by an increase in juvenile mortality and development time, combined with a decrease in adult size with temperature at low-resource supply. Our study suggests that most projections of temperature-dependent vector abundance and disease transmission are likely to be biased because they are based on traits measured under optimal resource supply. Our results provide compelling evidence for future studies to consider resource supply when predicting the effects of climate and habitat change on vector-borne disease transmission, disease vectors and other arthropods.

Traditional treatments for infectious disease have focused on the use of antimicrobial compounds (e.g. antibiotics) that target the infecting organism. However, timely diagnosis and administration of antibiotics remain crucial to ensure efficacy of these treatments especially for the highly virulent biothreat organisms.