Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis

Abstract

Following COVID-19 containment measures, healthcare service utilization was expected to decline, including in Kenya, across all healthcare tiers. We investigated the impact on community-level health indicators before and during the pandemic. This pre-post study examined community health utilization in 2019 (pre-pandemic) and 2020 (pandemic year) from March to December. Normality was assessed using the Shapiro-Wilk test, followed by Mann-Whitney U or Welch t-tests as appropriate. During the pandemic, facility deliveries (159.2 ± 39.0 vs 496.4 ± 288.2; +237.96%, P = .0232) and ANC referrals (191.0 ± 55.3 vs 630.1 ± 287.2; +229.89%, P = .0008) increased significantly. Child immunization referrals also rose (57.3 ± 11.7 vs 350.2 ± 259.3; +511.17%, P = .0060), while diarrhea treatments in children declined (59.2 ± 47.6 vs 9.2 ± 6.7; −84.46%, P = .0001). Diabetes referrals increased (108.7 ± 65.3 vs 319.5 ± 310.2; +211.15%, P = .035). Households with handwashing facilities saw a non-significant rise (78073.7 ± 16367.9 vs 118457.9 ± 90291.8; +51.73%, P = .3527). Community-level prevention and promotion programs persisted and were enhanced, due to increased fiscal and training support. Even amid crises, community health strategies can adapt and thrive with proper training and funding.

Keywords

community health public health COVID-19 pandemics health utilization delivery of health care

What is already known about this topic?

Community Health Services (CHS) are foundational to healthcare delivery in low- and middle-income countries, such as Kenya. Despite their critical role, CHS have historically been underfunded and under-recognized. The COVID-19 pandemic led to widespread disruptions in health services across sub-Saharan Africa, though the specific impact on CHS in Kenya remained insufficiently explored.

How does this research contribute to the field?

This study presents empirical evidence on CHS utilization during the COVID-19 pandemic in Kiambu County, Kenya. Contrary to broader regional trends of service disruption, the majority of CHS indicators in our study either improved or remained stable.

What are the implications for theory, practice, or policy?

The findings support systems-based public health models, emphasizing the stabilizing role of CHS. Practically, they underscore the importance of adequately training and equipping CHVs to maintain service continuity at the community level. Policy-wise, the results advocate for sustained investment in CHS, aligning with Kenya’s Primary Health Care Act (2023), and the goal of universal health coverage.

Introduction

Community health services (CHS) have long been an underrecognized pillar of health systems in low- and middle-income countries (LMICs).¹ This is unfortunate, as CHS play a crucial role in addressing society’s increasing health demands in the pursuit of universal health coverage.² In LMICs, this is frequently the initial level of healthcare, and it is made up of community health volunteers (CHVs) who work in community health units (CHUs).³ In this role, CHVs are intended to dispense preventive, promotive, curative and rehabilitative services within their communities.

CHVs offer maternal health services, including encouraging attendance at ante-natal and post-natal clinics (ANC and PNC, respectively).^3,4 Home-based PNC strategies include counseling on the importance of exclusive breastfeeding and providing family planning commodities. Child health services at the community level include referring immunization defaulters,³ supplementing Vitamin A,⁵ growth monitoring, and the treatment of diarrhea (the second leading cause of death in children under 5 years).^6,7 When allotted regularly, these community services have been shown to improve maternal and neonatal outcomes.^8
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CHVs also have an important referral role.³ They ensure that individuals with pre-existing diagnoses receive follow-up care and that older adults undergo regular check-ups to screen for emerging health concerns.

CHVs participate in quarterly dialog days to develop strategies for addressing unique community health challenges.³ Monitoring household access to clean water is another key responsibility of theirs.³

Before the COVID-19 pandemic, community health services in Kenya remained underfunded,¹¹ with CHVs operating voluntarily,¹² limiting both their numbers and overall impact.¹³

In March 2020, the COVID-19 pandemic began and disrupted healthcare delivery globally, including in Kenya, where CHVs were enlisted in the national COVID-19 Response Strategy. To continue their work while minimizing transmission risks, CHVs adopted “low-touch” protocols.¹⁴ To further curb the spread of COVID-19, public health measures such as lockdowns, hygiene promotion, dusk-to-dawn curfews and suspending public gatherings were among the changes implemented in Kenya.^15,16 The Ministry of Health in Kenya, therefore, integrated community health services to mitigate the anticipated strain on higher-tier health facilities.¹⁴ This approach aimed to prioritize vulnerable populations and avoid disruptions to their continuum of care.

During the pandemic, CHVs took on additional responsibilities, including contact tracing and educating community members about COVID-19.¹⁴ However, despite these expanded duties, CHVs remained unpaid volunteers, relying on government support through their supervisors for personal protective equipment (PPE), sanitizers, and other essential supplies.¹⁷

A review conducted by Tannor et al¹⁸ using 262 studies from 39 sub-Saharan Africa reported a general decline in healthcare utilization during the pandemic, though the extent varied by disease category and patient group. While this illustrates a widespread impact of the pandemic across the region, it did not explicitly indicate how the community health services fared in light of this pandemic. Because there were restrictions of movement,¹⁹ limited access to homes due to pandemic regulations and stigma, general poor funding to the community strategy by the local governments,¹ and a global lack of resources such as PPEs,²⁰ this study aimed to assess changes in community-level health service utilization in Kiambu County, Kenya. Kiambu County, located in central Kenya, had a population of over 795,000 households and 132 CHUs during the pandemic. It was also the second most affected county in Kenya based on COVID-19 case load.

Methods

Kiambu County (−1°10′0.01″S 36°49′59.99″E) is 1 of the 47 counties in the Republic of Kenya. It is the fifth most populous county in Kenya. The county has twelve (12) sub-counties and sixty (60) wards. As per the 2019 national census, it has a total population of 2,417,735 with 49.1% (1,187,146) males and 50.9% (1,230,454) females as well as 795,241 households. The number of community health units was 120 in 2018, 130 in 2019, and 285 in 2020.

This study employed a retrospective, descriptive, observational design. The pre-study period was defined as March to December 2019, with the post-study period spanning March to December 2020. The period from March to December 2019 was selected as the reference period due to its proximity to the onset of the pandemic and because it represents a time when data collection from community health units was most comprehensive and complete.

Data abstraction was done from the Kenya Health Information System (KHIS) on the 25th of January 2021 and can be found in Supplemental File 1. The KHIS is a nationwide system that collects de-identified, aggregated routine data from all health facilities, including the community level. At the point of collection by CHVs, the data is anonymized and comprises solely count data, e.g., how many people with wounds they referred for further treatment in a month. Each CHV submits this count data to their supervisor, who then aggregates the data and uploads it onto the KHIS.

The inclusion criteria for this study involved selecting only those indicators with complete, non-zero data, which were identified through purposive sampling. The exclusion criteria involved the removal of indicators that either lacked complete data or had zero values during the study period.

The community health indicators that were collected and analyzed have been described in Supplemental File 2. The variables of the study were grouped into 7 categories, namely: maternal services; family planning services; newborn and child health services; nutritional services; referral services and for people with injuries; water safety and access; and community health unit (CHU) activities.

Data were analyzed using R version 4.1.2 (Copyright © 2021 The R Foundation for Statistical Computing). To assess the effect of COVID-19, the performance before COVID-19 was subtracted from a similar period of 2020. Wilcoxon signed-rank test and Welch’s t-test were used to compare the 2 time periods, depending on if the data was not normally or normally distributed,respectively. To calculate the percentage change, we used a formula as described by Desta et al,²¹ where the total values for the indicator were subtracted from the corresponding period in 2020. The percentage change was calculated using the formula:

Percentage change = \frac{(PostCOVID 19 - PreCOVID 19)}{PreCOVID 19} \times 100 %

Unless otherwise stated, the results in the narrative are expressed as [PreCOVID-19 Monthly Mean ± S.D. vs COVID-19 Monthly Mean ± S.D.]. P ≤ .05 was considered significant.

This study assumes that the observed differences between the pre-pandemic and pandemic periods are primarily attributable to COVID-19. However, other potential confounders influencing data trends may not have been fully accounted for, which could introduce bias in attributing changes solely to the pandemic’s impact.

This study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting observational studies.²² The completed STROBE checklist is provided as Supplemental File 3.

Ethical approval was sought and granted by The University of Eastern Africa Baraton Ethics Committee (UEAB/REC/08/06/2020), which can be found in Supplemental File 4.

Results

Effects on Maternal Services

There were statistically significant increases in the reporting of the number of new deliveries that took place in a health facility [159.167 ± 38.978 vs 496.4 ± 288.2], the number of pregnant women referred to a health facility [191.00 ± 55.285 vs 630.1 ± 287.21], deliveries by skilled birth attendants [327.7 ± 66.094 vs 717.00 ± 271.07] and mothers with newborns counseled on exclusive breastfeeding [713.50 ± 762.28 vs 1182.70 ± 540.079]. This is summarized in Table 1.

Table 1.

Summary of Maternal, Newborn, Child Health, Nutrition, Referral, and Household Water Safety Services Before and During the COVID-19 Pandemic Year.

Community Health Indicator	Before pandemic year (10-month total)	During the pandemic year (10-month total)	Percentage change (%)	P-value
Maternal services
New deliveries that took place in health facility	1665	5627	237.96	.0232
Pregnant women referred to a health facility	1910	6301	229.89	.0008
Deliveries by SBA	3277	7170	118.79	.0013
Women with newborns counseled on EBF	7135	11 827	65.760	.0448
Under-age pregnancies	5691	1253	−77.98	.2116
Women provided with FP commodities	55 936	38 025	−32.03	.0448
Newborn & child health services
Children of 0 to 11 months referred for immunization	573	3502	511.17	.0060
Newborns visited within 48 h of delivery	12 772	3193	150	.3150
Immunization defaulter referred	90	190	37.58	.1220
Children of 12-59 months with diarrhea treated with Zinc and ORS	592	92	−84.46	.0001
Growth monitoring	48 914	55 535	13.536	.3859
Fever cases managed	6549	369	−94.36	.0013
Nutrition services
Children 6-59 months referred for Vitamin A supplementation	14 304	34 716	142.70	.1036
Children 12-59 months dewormed	300 834	157 598	−47.613	.0524
Referral services
Older persons referred for comprehensive services	2600	8262	217.77	.0052
Referred for chronic cough	532	297	−44.172	.0129
Diabetes	1165	3625	211.15	.0350
Hypertension	1945	4120	111.82	.1013
Cancer	78	274	251.28	.5365
Mental illness	298	601	101.67	.0580
Injuries and wounds managed	399	465	16.541	.5009
Household water safety and access
Functional latrines	1 336 448	1 309 260	−2.034	.3527
Hand washing facilities	780 737	1 184 579	51.73	.3527
New households accessing safe water	1 009 496	1 044 591	3.476	.8446

The number of underage pregnancies decreased during 2020 (125.3 ± 99.913) compared to 2019 (569.1 ± 694.15), but this was not statistically significant.

Effects on Family Planning (FP) Services

The number of women provided with FP commodities during the pandemic year (3802.5 ± 930.00) was statistically significantly lower than the year prior (5593.6 ± 2069.45; Table 1).

Effect on Newborn & Child Health Services

The number of children referred for immunization [57.3 ± 11.690 vs 350.2 ± 259.272] significantly increased during the COVID-19 pandemic year compared to before the pandemic, while children treated using zinc and ORS for diarrhea [59.2 ± 47.585 vs 9.2 ± 6.679] significantly decreased (Table 1).

There were no notable differences in the number of immunization defaulters [9.000 ± 6.149 vs 19.083 ± 20.214] and newborns visited at home within 48 h of delivery [1277.2 ± 1380.80 vs 3193.00 ± 4855.52]. Growth monitoring [4891.4 ± 2066.031 vs 5553.5 ± 1093.382] showed no notable change between the pre-pandemic and pandemic years, while the number of fever cases managed [654.9 ± 840.6392 vs 36.9 ± 22.18834] decreased significantly during the pandemic year.

Effect on Nutritional Services

The number of children aged 6 to 59 months referred for Vitamin A supplementation [1430.4 ± 681.371 vs 3471.6 ± 4649.48] showed no significant increase. Similarly, the number of children aged 12 to 59 months dewormed [30083.4 ± 13492.81 vs 15759.8 ± 17969.26] did not exhibit a significant change (Table 1).

Effects on Referral Services

The number of geriatrics referred for comprehensive health services increased significantly during the pandemic year [260.00 ± 97.265 vs 826.2 ± 603.04]. Similarly, the number of diabetic patients referred to health facilities for follow-up also increased significantly [108.667 ± 65.269 vs 319.5 ± 310.17]. In contrast, the number of referrals for coughs lasting 2 or more weeks decreased significantly [53.2 ± 22.493 vs 29.7 ± 13.646] during the pandemic year (Table 1).

Referrals for hypertensive patients [183.667 ± 69.931 vs 375.9 ± 309.85] did not show a meaningful change. Additionally, referrals for cancer [7.083 ± 4.420 vs 23.33 ± 31.90], mental illness [27.83 ± 9.320 vs 54.667 ± 43.573], and wound management [39.9 ± 18.980 vs 46.50 ± 23.684] showed percentage increases during the pandemic year but were not statistically significant.

Effects on Water Safety and Access

Despite there being a 51.73% increase in households with handwashing facilities during the pandemic year (118457.9 ± 90291.84) compared to the before (78073.7 ± 16367.94), this increase was not statistically significant. In addition, there was no statistically significant change in the number of households with functional latrines [133644.8 ± 35861.54 vs 130 926 ± 60780.41] or households visited in the month accessing safe water [100949.6 ± 23179.6 vs 104459.1 ± 50375.08] (Table 1).

Effects on Community Health Unit (CHU) Activities

Though not statistically significant, there were increases in CHUs issued with FP commodities [14.1 ± 6.045 vs 19.4 ± 22.157], CHVs expected to report [674.7 ± 114.510 vs 668.7 ± 236.045], community action days held [37.7 ± 10.562 vs 47.1 ± 59.238], and community dialog days held [22.4 ± 7.183 vs 26.2 ± 15.44].

Discussion

Pandemics have multifaceted effects on existing healthcare systems. Given that LMICs already contend with strained and poorly funded healthcare systems, the COVID-19 pandemic was thought to be the “straw that breaks the camel’s back.” In an attempt to cushion the impact on the entire healthcare system, part of the response included bolstering the community health strategy. However, given that the community level has been fraught with a myriad of incessant issues of its own,^2,16,23 this study aimed to establish the effect of COVID-19 on the utilization of health services at the community level in Kiambu county, Kenya.

Our findings demonstrate a rise in the key CHS utilization indicators during the COVID-19 pandemic. This is in stark contrast to studies conducted on other levels of the health system, which were found to be disrupted.^24,25 Their duties were largely performed following the Kenyan National Guidelines for Community Health Services (KNGCHS) issued during the COVID-19 lockdown, where they were supposed to deliver on routine CHS and COVID-19-specific roles.¹⁴ The reason for this observed effect is manifold, but what stands out is that CHS were prioritized and funded by external partners and supported by a policy framework. It can also be attributed to the additional training the CHVs received that increased their confidence in managing patients,²⁶ and this additional training served to mobilize them when the situation was dire.

Furthermore, providing CHVs with necessary equipment such as PPEs, as indicated by the KNGCHS, may have allowed them to feel safe while performing their duties during an uncertain period.¹⁶ Another reason that may point to the rise in referrals is that during the lockdown period, people were mandated to stay at home, which buttressed the modus operandi of the CHVs: visiting homes. This effect may have been compounded by community members generally trusting CHVs, as CHVs are nominated based on their social standing.³ On the other hand, the CHVs were to go out into the community and had more time to do so.

Both the number of pregnant women referred to health facilities and the number of deliveries conducted by a skilled attendant increased during the pandemic year. This is akin to a study conducted in Northern Ethiopia on the utilization of essential services that showed an 8-point rise in skilled delivery attendance.²¹ The number of women counseled on breastfeeding and provided FP commodities increased during the pandemic year in the present study. This is corroborated by studies on community-based care that have been shown to improve FP services and exclusive breastfeeding in Kenya, without the context of a pandemic.^8
-10 The number of under-age pregnancies reduced in Kiambu county during the pandemic year which was inconsistent with a study conducted in Western Kenya that showed deleterious effects on adolescent pregnancies as an effect of lockdown measures.²⁷ This difference may be due to regional differences. We showed that neonatal and child health services and nutrition services increased during the pandemic year. However, fewer children were treated for diarrhea. These results are consistent with a study conducted in Northern Ethiopia.²¹

More geriatrics, diabetics, and hypertensives were referred to a health facility. To our knowledge, this has not been previously reported on at the community level. A report by the World Health Organization found that 3 in every 4 countries reported that COVID-19 lockdown measures disrupted access and care for non-communicable disease,²⁸ which further underpins the importance of both these referral services and COVID-19 mitigation being provided at the community level.

The availability of running water and soap for hand-washing rose at the height of the pandemic and the use of leaky tins and other local adaptations of hand-washing stations increased in this study. This is inconsistent with a study conducted in Florida in the United States of America where there was a noted disruption in the availability of water for household purposes.²⁹ This finding also contradicts a study carried out to estimate the global access to handwashing facilities, which found that water insecurity increased throughout the world during the COVID-19 pandemic.³⁰ We attribute this to the success of the COVID-19 prevention activities carried out by CHVs and by public health officials during the pandemic, which nearly necessitated every household to have a water source to wash their hands.

There was an increase (albeit statistically insignificant) in the number of dialog and action days held in Kiambu County. To our knowledge, this has not been previously reported. We attribute this to the increased involvement of external non-governmental partners who provided additional training and support to CHVs.³¹

Our research highlights a significant limitation in the generation of CHS data. In 2020, 105 CHS indicators existed; however, our study included only key indicators with complete data across all months of the year. This is not a challenge unique to our study, but one that plagues many LMICs. This also affects the generalizability of our findings. The reliance on CHVs to self-report data based on their activities also introduces a potential source of bias.

Moreover, the aggregate nature of the data restricted our ability to account for potential confounders, which could have provided more nuanced insights into the factors influencing health service utilization.

Consequently, we advise conducting quarterly data quality audits and stepping up supported oversight at the county and subcounty levels. Instead of using manual data entry, we advise providing CHVs with reporting tools that connect directly to the Ministry of Health, Kenya’s computerized database. The Electronic Community Health Information System is a new program that the Government of Kenya (GOK) also launched in October 2023.^32,33 This can improve data collection and decrease errors in manual record-keeping. This will also be a huge step forward for planning, policy formation, monitoring, and evaluation.

CHS act as a bridge between formal health systems and communities and are an essential component of healthcare delivery, particularly in underserved areas in LMICs. CHUs provide services to 5000 or so individuals in a particular region, and 10 CHVs are available at each CHU to offer basic services related to curative, promotive, preventative, and rehabilitative care.³⁴ The ratio of 1 CHV to 500 community members is significant due to the recent implementation of the Primary Health Act in Kenya in October 2023³⁵ (p. 13). Increasing CHS coverage ought to be a top priority in each county.

To prevent the loss of the progress made with CHS service, CHVs, who in Kenya will now be referred to as Community Health Promoters (CHPs) as of October 2023 under the Primary Health Care Act, should get appropriate compensation. On average, CHPs are to receive a stipend of 7500 per month from March 2024 (US$50.00).³⁶ Although this is a positive development, we would be negligent if we disregarded the fact that CHS provision involves caring for about 500 individuals and serve as the initial point of contact for Kenya’s healthcare system. Furthermore, it is significant to remember that, as of February 22, 2024, the minimum wage in Kenya was KES 15,201 (US$ 101.34) per month. Therefore, even though CHPs are now supported to maintain their financial standing while performing their respective duties, and this approach can improve recruitment and delay attrition,¹⁶ it’s possible that this does not always translate into compensation that corresponds to the work done. Ultimately, these roles are no longer voluntary positions – nor should they be – and their remuneration and benefits should reflect the same.

We also wish to highlight the necessity of recognizing and addressing the long-standing financial and prioritization inadequacies in Kenya’s healthcare system. Even though CHPs are at the bottom of the healthcare hierarchy, their work invariably creates demand by way of patient referrals that move up the system. As a result, it is imperative to support and provide additional funding for higher levels of healthcare through growing the healthcare industry’s human resources, finances, infrastructure, and health information systems. In the fiscal year of 2023 to 2024, the Ministry of Health was allocated 11% of the yearly budget, which falls short of the 15% stipulated during the Abuja Declaration.³⁷ This is not an isolated incident, as the budget for healthcare has been reducing in Kenya, and is a cause for concern. The government must give priority to healthcare to strengthen and maintain the healthcare system at all levels.

To strengthen the referral system, we advocate a referral form filing system for traceability of referral clients both to and from the link facilities. This, in our opinion, would also facilitate the realization of UHC.

Conclusion

The COVID-19 pandemic underscored the critical role of CHS in sustaining healthcare delivery during periods of crisis. Our findings indicate that, despite the immense documented strain on healthcare systems as a result of the pandemic, CHS in Kiambu County not only remained operational but saw increased utilization. We largely attribute this to strategic investments in training, resource allocation, and policy support. The engagement of CHVs, coupled with enhanced financial and logistical backing, was instrumental in maintaining essential services, underscoring the effectiveness of community-level interventions in mitigating healthcare disruptions. These results highlight the need for sustained investment in CHS, not only as a crisis response mechanism but as a cornerstone of primary healthcare. Future research should examine post-pandemic CHS performance, particularly in the context of UHC implementation. Strengthening CHS through adequate compensation, digital health integration, and structured oversight will be crucial in ensuring long-term resilience and equity in healthcare delivery.

Supplemental Material

sj-pdf-2-inq-10.1177_00469580251338681 – Supplemental material for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis

Supplemental material, sj-pdf-2-inq-10.1177_00469580251338681 for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis by Prabhjot Kaur Juttla, Bernard Kimani, Moses Kamita, Teresia Kariuki, Naomi Wachira, Alfred Owino Odongo and Magoma Mwancha-Kwasa in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Supplemental Material

sj-pdf-3-inq-10.1177_00469580251338681 – Supplemental material for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis

Supplemental material, sj-pdf-3-inq-10.1177_00469580251338681 for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis by Prabhjot Kaur Juttla, Bernard Kimani, Moses Kamita, Teresia Kariuki, Naomi Wachira, Alfred Owino Odongo and Magoma Mwancha-Kwasa in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Supplemental Material

sj-pdf-4-inq-10.1177_00469580251338681 – Supplemental material for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis

Supplemental material, sj-pdf-4-inq-10.1177_00469580251338681 for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis by Prabhjot Kaur Juttla, Bernard Kimani, Moses Kamita, Teresia Kariuki, Naomi Wachira, Alfred Owino Odongo and Magoma Mwancha-Kwasa in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Supplemental Material

sj-xlsx-1-inq-10.1177_00469580251338681 – Supplemental material for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis

Supplemental material, sj-xlsx-1-inq-10.1177_00469580251338681 for Assessing the Effect of the COVID-19 Pandemic on Community Health Services: A Pre-post Analysis by Prabhjot Kaur Juttla, Bernard Kimani, Moses Kamita, Teresia Kariuki, Naomi Wachira, Alfred Owino Odongo and Magoma Mwancha-Kwasa in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

We would like to acknowledge Central Province Response Integration Strengthening and Sustainability Project and Elizabeth Glaser Pediatric AIDS Foundation for feedback and logistical support.

ORCID iD

Prabhjot Kaur Juttla

Ethical Considerations

Ethical approval for this study was obtained from the University of Eastern Africa Baraton Ethics Committee (UEAB/REC/08/06/2020). The approval was granted for the period from June 11, 2020, to June 10, 2021, and data abstraction was conducted within this timeframe on January 25, 2021. The ethical approval document has been uploaded as .

Consent to Participate

This study involved secondary data analysis; therefore, informed consent was not required. At no point did the authors have access to any identifiable information related to individuals or communities. The data were obtained from the Kenya Health Information System (KHIS), a nationwide platform that collects de-identified, aggregated routine health data from all health facilities, including those at the community level. Data collected by Community Health Volunteers are anonymized at the point of collection and consist solely of count-based information.

Author Contributions

PKJ conducted the data analysis and interpretation, drafted the initial manuscript, drafted and finalized the final manuscript. BK was responsible for data collection, contributed to the discussion, and contributed to the methodology. MK provided oversight to the data analysis, providing critical insights into the findings. TK contributed resources and provided oversight throughout the study. NW assisted with data collection and contributed to the methodological framework. AOO provided oversight, reviewed and critiqued the initial manuscript, and contributed resources for the execution of the study. MMK conceptualized the study, provided resources throughout the study, oversaw the project, and played a key role in developing the methodology. Each author approved the final version to be published and participated sufficiently in the work to take public responsibility for appropriate portions of the content.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data underlying this research can be found in the Supplemental files, S1.

Supplemental Material

Supplemental material for this article is available online.

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