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. 2021 Jul 26;21(1):740.
doi: 10.1186/s12913-021-06726-4.

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

Edwine Barasa  1   2 , Jacob Kazungu  3 , Stacey Orangi  3 , Evelyn Kabia  3 , Morris Ogero  4 , Kadondi Kasera  5
Affiliations

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

Edwine Barasa et al. BMC Health Serv Res. .

Abstract

Background: The 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.

Methods: We 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.

Results: Quantitative 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.

Conclusion: Finding 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.

Keywords: COVID-19; Indirect health effects; Kenya; Pandemic.

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Conflict of interest statement

All authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Daily incidence of COVID-19 cases in Kenya
Fig. 2
Fig. 2
Interrupted time series of monthly OPD utilisation in Kenya from January 2019 to November 2020
Fig. 3
Fig. 3
Interrupted time series of monthly bed occupancy rate in Kenya Jan 2019 to November 2020
Fig. 4
Fig. 4
Interrupted time series of 4 ANC coverage in Kenya from January 2019 to November 2020
Fig. 5
Fig. 5
Interrupted time series of monthly number of deliveries in health facilities in Kenya from January 2019 to November 2020
Fig. 6
Fig. 6
Interrupted time series of monthly Measles vaccination coverage in Kenya Jan 2019 to November 2020
Fig. 7
Fig. 7
Interrupted time series of monthly DPT 3 vaccination coverage in Kenya Jan 2019 to November 2020
Fig. 8
Fig. 8
Interrupted time series of sexual violence cases per OPD visits in Kenya from January 2019 to November 2020
See this image and copyright information in PMC

References

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