Evidence map›Paper›PMID 41333574›Full record

ArticleFrontiers in global women's health2025

Maternal and child health services during the COVID-19 pandemic in India: an interrupted time-series analysis.

Stuti Tripathi, Pravin Kumar Singh, Lucky Singh, Ravleen Kaur Bakshi, Tulsi Adhikari, Saritha Nair, Kh Jitenkumar Singh, Ashoo Grover, Saurabh Sharma

Abstract read
In one paragraph

Article in Frontiers in global women's health, 2025. 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
–field-weighted citation impact
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

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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.

  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

9 authors.

Stuti Tripathi *ICMR-National Institute for Research in Digital Health and Data Science, New Delhi, India.
Pravin Kumar Singh *ICMR-National Institute for Research in Digital Health and Data Science, New Delhi, India.
Lucky Singh *ICMR-Headquarters, New Delhi, India.
Ravleen Kaur BakshiICMR-Headquarters, New Delhi, India.
Tulsi AdhikariICMR-Headquarters, New Delhi, India.
Saritha NairICMR-Headquarters, New Delhi, India.
Kh Jitenkumar SinghICMR-Headquarters, New Delhi, India.
Ashoo GroverICMR-Headquarters, New Delhi, India.
Saurabh SharmaICMR-Headquarters, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The COVID-19 pandemic posed significant challenges to healthcare systems worldwide. Maintaining essential health services, including maternal and child health (MCH), while addressing the pandemic is an enormous task. This study aimed to assess the impact of the COVID-19 pandemic on the utilization of MCH services in India's public primary care. It extends prior work by applying nationwide HMIS data within an interrupted time-series framework with seasonal and ARMA adjustments to estimate counterfactual trends, thereby providing national-level insights into both immediate and evolving disruptions. Methods: A retrospective analysis using Health Management Information System (HMIS) data examined 12 indicators of service utilization, covering maternal health, child health, deliveries, and newborn care. Interrupted time-series analysis compared pre-pandemic (April 2017-March 2020) and pandemic (March 2020-May 2021) was performed using Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) regression models, adjusting for seasonality and autocorrelation with ARMA terms. Results: Antenatal care (ANC) registrations decreased by 346,420 cases (-12.8%, Conclusions: The COVID-19 pandemic caused declines in MCH service utilization, with varying recovery across indicators. While services like antenatal care and vaccinations showed some stabilization over time, child health admissions and obstetric complications remained below pre-pandemic trends. Strengthening healthcare systems to maintain essential services and support recovery during and after public health emergencies is critical.

Indexed as

coronavirus diseasehealth management information systemIndiainterrupted time series analysismaternal and child health

Identifiers

PMID41333574
PMCPMC12665747

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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.