Visceral leishmaniasis cyclical trends in Bihar, India – implications for the elimination programme version 1; peer review: 1 approved, 2 approved with reservations

• Published in: Gates open research
• Main Authors: Deb, Rinki M, Stanton, Michelle C, Foster, Geraldine M, Das Gupta, Rudra K, Roy, Nupur, Das, Pradeep, Dhariwal, Akshay C, Coleman, Michael
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis Ltd 21.02.2018
• Subjects: Censuses; Epidemics; Humidity; Insecticides; Malaria; Monsoons; Mortality; Parasitic diseases; Population; Public health; Trends; Tropical diseases; Wind; West Bengal India; Nepal; India
• DOI: 10.12688/gatesopenres.12793.1
• ISSN: 2572-4754

Background: Visceral leishmaniasis (VL) is a vector-borne disease of public health importance in India, with the highest burden of disease in the states of Bihar, Jharkhand, West Bengal and Uttar Pradesh. The disease is currently targeted for elimination (annual incidence to less than one per 10,000 population) using indoor residual spraying, active case detection and treatment. Historically the disease trend in India has been regarded as cyclical with case resurgence characteristically occurring every 15 years. Understanding this pattern is essential if the VL elimination gains are to be sustained. To better understand the cyclical trends, annual climatic indicators including rainfall, temperature and humidity over time were compared with annual VL case incidence data. Methods: Annual climate data (rainfall, average and maximum temperature and specific humidity) from 1956-2004 were used to identify potential factors influencing VL incidence. Months relevant to the VL life-cycle were identified and defined (Monsoon, Sand-fly Peak, Pre-Sand-fly Peak and Annual) for analysis. The Kruskall-Wallis test was used to determine significant difference between categorical rainfall and VL incidence, whilst univariate negative binomial regression models were used to determine predictors of disease incidence. Results: The negative binomial regression model showed statistically significant associations (p <0.05) for VL incidence and maximum temperature, and average temperature, when considering annual and pre-sand fly peak time periods. No other associations between humidity, rainfall or temperature and VL incidence were detected (all values p >0.05). Conclusion: The VL programme in Bihar has made significant progress in adopting best practices for improved treatment and vector control, with the aim to achieve VL elimination. However, open access granular programme data for indoor residual spray activities and case detection is required to fully understand the role of climate in disease transmission and potential resurgence.