Evidence map›Paper›PMID 35561500›Full record

ArticleEpidemics2022

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

Vijay Kumar, Niyamat A Siddiqui, Timothy M Pollington, Rakesh Mandal, Sushmita Das, Shreekant Kesari, Vidyanand R Das, Krishna Pandey, T Déirdre Hollingsworth, Lloyd A C Chapman and 1 more

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 3 countries.

Vijay KumarRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India.
Niyamat A SiddiquiRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India.
Timothy M PollingtonMathSys - Mathematics for Real-World Systems Centre for Doctoral Training, University of Warwick, Coventry CV4 7AL, UK; Big Data Institute (BDI), University of Oxford, Oxford OX3 7LF, UK; Centre for Tropical Medicine and Global Health, University of Oxford, Oxford OX3 7LG, UK; Mahidol-Oxford Tropical Medicine Research Unit (MORU), Mahidol University, Bangkok 10400, Thailand.
Rakesh MandalRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India.
Sushmita DasAll India Institute of Medical Sciences (AIIMS), Patna 801507, India.
Shreekant KesariRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India.
Vidyanand R DasRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India.
Krishna PandeyRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India.
T Déirdre HollingsworthBig Data Institute (BDI), University of Oxford, Oxford OX3 7LF, UK.
Lloyd A C ChapmanCentre for Mathematical Modelling of Infectious Diseases (CMMID), London School of Hygiene & Tropical Medicine (LSHTM), London WC1H 9SH, UK.
Pradeep DasRajendra Memorial Research Institute of Medical Sciences (RMRIMS) (ICMR), Patna 800007, India; National Institute of Cholera and Enteric Diseases (NICED) (ICMR), Kolkata 700010, India. Electronic address: drpradeep.das@gmail.com.
Rajendra Memorial Research Institute of Medical Sciences · INAll India Institute of Medical Sciences · INLondon School of Hygiene & Tropical Medicine · GBMahidol University · THOpen Data Institute · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Leishmaniasis, VisceralHumansIncidenceIndiaInterrupted Time Series AnalysisDistributed-lagEliminationIntegrated controlKala-azarRegression discontinuitySpatiotemporal

Identifiers

PMID35561500
PMCPMC9188270
OpenAlexW4224303089

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.