Socio‐ecological dynamics in urban systems: An integrative approach to mosquito‐borne disease in Bengaluru, India

Quantifying climatic and socioeconomic drivers of urban malaria in Surat, India: a statistical spatiotemporal modelling study

BACKGROUND

Cities are becoming increasingly important habitats for mosquito vectors of disease. The pronounced heterogeneity of urban landscapes challenges our understanding of the effects of climate and socioeconomic factors on mosquito-borne disease dynamics at different spatiotemporal scales. Here, we quantify the impact of climatic and socioeconomic factors on urban malaria risk, using an extensive dataset in both space and time for reported Plasmodium falciparum cases in the city of Surat, northwest India.

METHODS

We analysed 10 years of monthly P falciparum cases resolved at three nested spatial resolutions (seven zones, 32 units, and 478 worker units) with a Bayesian hierarchical mixed model that incorporates the effects of population density, poverty, relative humidity, and temperature, in addition to random effects (structured and unstructured). To reduce dimensionality and avoid correlation of covariates, socioeconomic variables from survey data were summarised into main axes of variation using principal component analysis. With model selection, we identified the main drivers of spatiotemporal variation in malaria incidence rates at each of the three spatial resolutions. We also compared observations to model-fitted cases by quantifying the percentage of predictions within five discrete levels of malaria risk.

FINDINGS

The spatial variation of urban malaria cases was stationary over time, whereby locations with high and low yearly cases remained largely consistent across years. Local socioeconomic variation could be summarised with three principal components accounting for approximately 80% of the variance. The model that incorporated local temperature and relative humidity together with two of these principal components, largely representing population density and poverty, best explained monthly malaria patterns in models formulated at the three different spatial scales. As model resolution increased, the effect size of humidity decreased, whereas those of temperature and the principal component associated with population density increased. Model predictions accurately captured aggregated total monthly cases for the city; in space-time, they more closely matched observations at the intermediate scale, with around 57% of units estimated to fall in the observed category on average across years. The mean absolute error was lower at the intermediate level, showing that this is the best aggregation level to predict the space-time dynamics of malaria incidence rates across the city with the selected model.

INTERPRETATION

This statistical modelling framework provides a basis for development of a climate-driven early warning system for urban malaria for the units of Surat, including spatially explicit prediction of malaria risk several weeks to months in advance. Results indicate environmental and socioeconomic covariates for which further measurement at high resolution should lead to model improvement. Advanced warning combined with local surveillance and knowledge of disease hotspots within the city could inform targeted intervention as part of urban malaria elimination efforts.

FUNDING

US National Institutes of Health.

The mismatch of narratives and local ecologies in the everyday governance of water access and mosquito control in an urbanizing community

Mosquito-borne disease presents a significant threat to urban populations, but risk can be uneven across a city due to underlying environmental patterns. Urban residents rely on social and economic processes to control the environment and mediate disease risk, a phenomenon known as everyday governance. We studied how households employed everyday governance of urban infrastructure relevant to mosquito-borne disease in Bengaluru, India to examine if and how inequalities in everyday governance manifest in differences in mosquito control. We found that governance mechanisms differed for water access and mosquitoes. Economic and social capital served different roles for each, influenced by global narratives of water and vector control.

Examining the paradox of urban disease ecology by linking the perspectives of Urban One Health and Ecology with Cities

The ecology of zoonotic, including vector-borne, diseases in urban social-ecological systems is influenced by complex interactions among human and environmental factors. Several characteristics contribute to the emergence and spread of infectious diseases in urban places, such as high human population densities, favorable habitat for vectors, and humans' close proximity to animals and their pathogens. On the other hand, urban living can contribute to the improvement of public health through better access to health services and creation of ecological and technological infrastructure that reduces disease burdens. Therefore, urbanization creates a disease ecology paradox through the interplay of urban health penalties and advantages for individual and community outcomes. To address this contradiction, we advocate a holistic Urban One Health perspective for managing urban systems, especially their green spaces and animal populations, in ways that more effectively control the spread of zoonotic diseases. This view should be coupled with an Ecology with Cities approach which emphasizes actionable science needed for urban planning, management and policymaking; developing disease and vector surveillance programs using citizen and community science methods; and improving education and communication actions that help diverse stakeholders understand the complexities of urban disease ecology. Such measures will enable scholars from many disciplines to collaborate with professionals, government officials, and others to tackle challenges of the urban disease paradox and create more sustainable, health-promoting environments.