Predicting disease risk areas through co-production of spatial models: The example of Kyasanur Forest Disease in India's forest landscapes.

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings.

Coverage and effectiveness of Kyasanur forest disease (KFD) vaccine in Karnataka, South India, 2005-10.

BACKGROUND: Kyasanur forest disease (KFD), a tick-borne viral disease with hemorrhagic manifestations, is localised in five districts of Karnataka state, India. Annual rounds of vaccination using formalin inactivated tissue-culture vaccine have been conducted in the region since 1990. Two doses of vaccine are administered to individuals aged 7-65 years at an interval of one month followed by periodic boosters after 6-9 months. In spite of high effectiveness of the vaccine reported in earlier studies, KFD cases among vaccinated individuals have been recently reported. We analysed KFD vaccination and case surveillance data from 2005 to 2010. METHODOLOGY/PRINCIPAL FINDINGS: We calculated KFD incidence among vaccinated and unvaccinated populations and computed the relative risk and vaccine effectiveness. During 2005-2010, a total of 343,256 individuals were eligible for KFD vaccination (details of vaccination for 2008 were not available). Of these, 52% did not receive any vaccine while 36% had received two doses and a booster. Of the 168 laboratory-confirmed KFD cases reported during this 5-year period, 134 (80%) were unvaccinated, nine each had received one and two doses respectively while 16 had received a booster during the pre-transmission season. The relative risks of disease following one, two and booster doses of vaccine were 1.06 (95% CI = 0.54-2.1), 0.38 (95% CI = 0.19-0.74) and 0.17 (95% CI = 0.10-0.29) respectively. The effectiveness of the vaccine was 62.4% (95% CI = 26.1-80.8) among those who received two doses and 82.9% (95% CI = 71.3-89.8) for those who received two doses followed by a booster dose as compared to the unvaccinated individuals. CONCLUSIONS: Coverage of KFD vaccine in the study area was low. Observed effectiveness of the KFD vaccine was lower as compared to the earlier reports, especially after a single dose administration. Systematic efforts are needed to increase the vaccine coverage and identify the reasons for lower effectiveness of the vaccine in the region.