Evidence map›Paper›PMID 34311716›Full record

ArticleBMC health services research2021

Indirect health effects of the COVID-19 pandemic in Kenya: a mixed methods assessment.

Edwine Barasa, Jacob Kazungu, Stacey Orangi, Evelyn Kabia, Morris Ogero, Kadondi Kasera

Abstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 2 pooled it
–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

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

73 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. A situational and stakeholder analysis of health technology assessment in Zimbabwe.International journal of technology assessment in health care · 2024
    Article
  19. Article
  20. Article

13 more citing papers are in PubMed but not listed here.

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.

Edwine BarasaHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya. ebarasa@kemri-wellcome.org.
Jacob KazunguHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Stacey OrangiHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Evelyn KabiaHealth Economics Research Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Morris OgeroHealth Services Unit, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya.
Kadondi KaseraMinistry of Health, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic and country measures to control it can lead to negative indirect health effects. Understanding these indirect health effects is important in informing strategies to mitigate against them. This paper presents an analysis of the indirect health effects of the pandemic in Kenya.

methodsWe employed a mixed-methods approach, combining the analysis of secondary quantitative data obtained from the Kenya Health Information System database (from January 2019 to November 2020) and a qualitative inquiry involving key informant interviews (n = 12) and document reviews. Quantitative data were analysed using an interrupted time series analysis (using March 2020 as the intervention period). Thematic analysis approach was employed to analyse qualitative data.

resultsQuantitative findings show mixed findings, with statistically significant reduction in inpatient utilization, and increase in the number of sexual violence cases per OPD visit that could be attributed to COVID-19 and its mitigation measures. Key informants reported that while financing of essential health services and domestic supply chains were not affected, international supply chains, health workforce, health infrastructure, service provision, and patient access were disrupted. However, the negative effects were thought to be transient, with mitigation measures leading to a bounce back.

conclusionFinding from this study provide some insights into the effects of the pandemic and its mitigation measures in Kenya. The analysis emphasizes the value of strategies to minimize these undesired effects, and the critical role that routine health system data can play in monitoring continuity of service delivery.

Indexed as

COVID-19PandemicsHumansKenyaQualitative ResearchSARS-CoV-2COVID-19Indirect health effectsKenyaPandemic

Identifiers

PMID34311716
PMCPMC8311400

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.