Evidence map›Paper›PMID 35545289›Full record

ArticleBMJ global health2022

'Imperfect but useful': pandemic response in the Global South can benefit from greater use of mathematical modelling.

Sandip Mandal, Kanchan Parchani, Nimalan Arinaminpathy, Swarup Sarkar, Balram Bhargava, Samiran Panda

Open access · goldAbstract read
In one paragraph

Article in BMJ global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
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

6 authors at 3 institutions in 3 countries.

Sandip MandalDivision of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India.ORCID 0000-0001-5651-8632
Kanchan ParchaniMRC Centre for Global Infectious Disease Analysis, and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College, London, UK.
Nimalan ArinaminpathyMRC Centre for Global Infectious Disease Analysis, and the Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College, London, UK.ORCID 0000-0001-9502-6876
Swarup SarkarSchool of Public Health and Community Medicine, University of Gothenburg, Goteborg, Sweden.ORCID 0000-0002-0311-0710
Balram BhargavaIndian Council of Medical Research, New Delhi, India.
Samiran PandaDivision of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India pandasamiran@gmail.com.ORCID 0000-0002-5077-6275
Indian Council of Medical Research · INImperial College London · GBUniversity of Gothenburg · SE

Funding

Medical Research Council MR/R015600/1
6 · The paper itself

Abstract

Mathematical modelling has been a helpful resource for planning public health responses to COVID-19. However, there is a need to improve the accessibility of models built within country contexts in the Global South. Immediately following the overwhelming 'second wave' of COVID-19 in India, we developed a user-friendly, web-based modelling simulator in partnership with the public health experts and health administrators for subnational planning. The purpose was to help policy-makers and programme officials at the state and district levels, to construct model-based scenarios for a possible third wave. Here, we describe our experiences of developing and deploying the simulator and propose the following recommendations for future such initiatives: early preparation will be the key for pandemic management planning, including establishment of networks with potential simulator users. Ideally, this preparedness should be conducted during 'peace time', and coordinated by agencies such as WHO. Second, flexible modelling frameworks will be needed, to respond rapidly to future emergencies as the precise nature of any pandemic is impossible to predict. Modelling resources will, therefore, need to be rapidly adaptable to respond as soon as a novel pathogen emerges. Third, limitations of modelling must be communicated clearly and consistently to end users. Finally, systematic mechanisms are required for monitoring the use of models in decision making, which will help in providing modelling support to those local authorities who may benefit most from it. Overall, these lessons from India can be relevant for other countries in the South-Asian-Region, to incorporate modelling resources into their pandemic preparedness planning.

Indexed as

COVID-19PandemicsHumansIndiaModels, TheoreticalPublic Healthcontrol strategiesCOVID-19health policyhealth services researchmathematical modelling

Identifiers

PMID35545289
PMCPMC9096499
OpenAlexW4280552810

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.