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.

Lymphatic filariasis elimination endgame in an urban Indian setting: the roles of surveillance and residual microfilaremia after mass drug administration.

BACKGROUND: To secure the gains of lymphatic filariasis (LF) elimination programs, attention is needed to the 'residual microfilaremia phase', in which high-risk populations may be crucial. The present study documents the impact of mass drug administration (MDA) in the urban Indian setting of Surat City, with high rates of in-migration. METHODS: Epidemiological assessment included National Filaria Control Program (NFCP) and World Health Organization recommended routine and pre-MDA microfilaremia surveys respectively. Routine filaria surveys were conducted around the year in approximately 2000-4000 people per month, while pre-MDA surveys were carried out annually among approximately 4000 people from four fixed and four random sites. In 2016, Transmission Assessment Survey (TAS) was done in primary school children. The outcomes were microfilaremia (Mf) and antigen prevalence; more specifically, microfilaremia according to place of birth, in pre-MDA and routine night blood smears (NBS) collected from 2008 to 2015. Prevalence ratios and confidence intervals were calculated. RESULTS: A total of 25 480 pre-MDA and 306 198 routine NBS were examined during the study. In 2008, the Mf prevalence in the routine survey was 63/18 814 (0.33%), declining to 23/39 717 (0.06%) in 2016. Pre-MDA surveys showed a similar decrease from 47/4184 (1.1%) in 2008 to 12/4042 (0.3%) in 2015. In those born outside Surat, microfilaremia decreased below transmission thresholds, but remained more than treble that of the remainder of the population, in both the pre-MDA surveys [prevalence ratio: 3.17, 95% confidence interval (CI): 1.15-8.72], and the routine surveys (3.31, 95% CI: 1.47-7.48). Though the TAS results indicated that MDA endpoints had been reached, sub-group analysis identified that 90% of antigenemic children were from families of high-risk groups. CONCLUSIONS: Extensive long-term epidemiological monitoring suggests that all the urban population, including high-risk groups, have benefitted from the ELF program. To prevent re-establishment of infection in large urban areas with unsanitary conditions conducive to filarial vector breeding, there is need to identify residual microfilaremia by customized surveys in addition to pre-MDA monitoring and TAS. The present findings can be used to develop strategies to prioritize screening, surveillance and plan treatment of high-risk groups after achieving MDA endpoints.