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. 2022 Jun:39:100562.
doi: 10.1016/j.epidem.2022.100562. Epub 2022 Apr 21.

Impact of intensified control on visceral leishmaniasis in a highly-endemic district of Bihar, India: an interrupted time series analysis

Vijay Kumar  1 , Niyamat A Siddiqui  1 , Timothy M Pollington  2 , Rakesh Mandal  1 , Sushmita Das  3 , Shreekant Kesari  1 , Vidyanand R Das  1 , Krishna Pandey  1 , T Déirdre Hollingsworth  4 , Lloyd A C Chapman  5 , Pradeep Das  6
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Impact of intensified control on visceral leishmaniasis in a highly-endemic district of Bihar, India: an interrupted time series analysis

Vijay Kumar et al. Epidemics. 2022 Jun.

Abstract

Visceral leishmaniasis (VL) is declining in India and the World Health Organization's (WHO) 2020 'elimination as a public health problem' target has nearly been achieved. Intensified combined interventions might help reach elimination, but their impact has not been assessed. WHO's Neglected Tropical Diseases 2021-2030 roadmap provides an opportunity to revisit VL control strategies. We estimated the combined effect of a district-wide pilot of intensified interventions in the highly-endemic Vaishali district, where cases fell from 3,598 in 2012-2014 to 762 in 2015-2017. The intensified control approach comprised indoor residual spraying with improved supervision; VL-specific training for accredited social health activists to reduce onset-to-diagnosis time; and increased Information Education & Communication activities in the community. We compared the rate of incidence decrease in Vaishali to other districts in Bihar state via an interrupted time series analysis with a spatiotemporal model informed by previous VL epidemiological estimates. Changes in Vaishali's rank among Bihar's endemic districts in terms of monthly incidence showed a change pre-pilot (3rd highest out of 33 reporting districts) vs. during the pilot (9th) (p<1e-10). The rate of decline in Vaishali's incidence saw no change in rank at 11th highest, both pre-pilot & during the pilot. Counterfactual model simulations suggest an estimated median of 352 cases (IQR 234-477) were averted by the Vaishali pilot between January 2015 and December 2017, which was robust to modest changes in the onset-to-diagnosis distribution. Strengthening control strategies may have precipitated a substantial change in VL incidence in Vaishali and suggests this approach should be piloted in other highly-endemic districts.

Keywords: Distributed-lag; Elimination; Integrated control; Kala-azar; Regression discontinuity; Spatiotemporal.

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: VK, NAS, SK, VNRD, KP & PD were the permanent employees of RMRIMS. RM was a Ph.D. student under its Dept. of Vector Biology. They initiated this institutional study on the instruction of the Directorate General of Health Services, Ministry of Health & Family Welfare, Govt. of India. PD had full access to the data and final responsibility for publication submission. TDH, LACC & TMP have no conflicts of interest.

Figures

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Graphical abstract
Fig. 1
Fig. 1
Study map & timeline. (a) The pilot district of Vaishali is the hatched region. GADM shapefile (GADM, 2015). (b) Annotations indicate the start months of the intensified control elements and circular dots mark the biannual accredited social health activist (ASHA) training, indoor residual spraying (IRS) training rounds, and information, education & communication activities (IEC). The hatched bar marks the period of pilot scale-up when the combined methods would unlikely have reached full impact. Made in ArcMap™.
Fig. 2
Fig. 2
Visceral leishmaniasis time series for Vaishali district and the rest of Bihar state. Monthly case counts (Government of India, 2017). Note that HIV-VL cases are included from 2015–2016 and HIV/TB-VL from 2017; monthly VL-HIV/TB case proportions are shown in SI Fig. S9. The state mean excludes Aurangabad, Gaya, Jamui, Kaimur, Rohtas & Vaishali districts. The dashed vertical line indicates the start of the modelled intervention.
Fig. 3
Fig. 3
Effective reproduction number Rˆe(t) for Vaishali & 32 other districts as means (a) and as 33 separate districts (b). The inferred infection times on the x axes was calculated by subtracting the mean incubation period and mean onset-to-diagnosis time (7-month total shift) from the diagnosis month. The dashed vertical line indicates the length of the 7-month sliding window used to smooth the Rˆe estimates: before this date estimates are unreliable as they only include partial data within this sliding interval. The dotted vertical line indicates the start of the modelled intervention.
Fig. 4
Fig. 4
Estimated cumulative cases averted since the pilot start.
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