About the Author(s)


Anthony Waruru Email symbol
Division of Global HIV and TB, US Centers for Disease Control and Prevention (CDC), Nairobi, Kenya

Jonesmus M. Wambua symbol
Global Programs for Research and Training, University of California, Nairobi, Kenya

Frank V. Otieno symbol
Department of Health Records, Mbagathi County Referral Hospital, Nairobi, Kenya

Mary Mwangome symbol
Global Programs for Research and Training, University of California, Nairobi, Kenya

Peninah Munyua symbol
Division of Global Health Protection, US Centers for Disease Control and Prevention (CDC), Nairobi, Kenya

Wanjiru Waruiru symbol
Global Programs for Research and Training, University of California, Nairobi, Kenya

Sasi Jonnalagadda symbol
Division of Global HIV and TB, US Centers for Disease Control and Prevention (CDC), Nairobi, Kenya

Carol Ngunu symbol
Nairobi County Department of Health, Nairobi, Kenya

Annastacia K. Muange symbol
Division of Disease Surveillance and Response (DDSR), Ministry of Health, Nairobi, Kenya

James Otieno symbol
Kisumu County Department of Health, Kisumu, Kenya

Dickens Onyango symbol
Kisumu County Department of Health, Kisumu, Kenya

Nelly Muturi symbol
AIRBEL Impact Lab, International Rescue Committee (IRC), Nairobi, Kenya

Anne Njoroge symbol
International Training and Education Center for Health (I-TECH), University of Washington, Nairobi, Kenya

Citation


Waruru A, Wambua JM, Otieno FV, et al. Hypoxia predicts COVID-19 mortality: Evidence to inform low-resource care. J Public Health Africa. 2025;16(1), a1454. https://doi.org/10.4102/jphia.v16i1.1454

Original Research

Hypoxia predicts COVID-19 mortality: Evidence to inform low-resource care

Anthony Waruru, Jonesmus M. Wambua, Frank V. Otieno, Mary Mwangome, Peninah Munyua, Wanjiru Waruiru, Sasi Jonnalagadda, Carol Ngunu, Annastacia K. Muange, James Otieno, Dickens Onyango, Nelly Muturi, Anne Njoroge

Received: 26 May 2025; Accepted: 05 Sept. 2025; Published: 02 Dec. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: Hypoxia is a critical yet under-recognised driver of poor outcomes in coronavirus disease 2019 (COVID-19). Early detection with cheap pulse oximetry is feasible in resource-limited settings.

Aim: This study estimated the prevalence of hypoxia at admission and its role in predicting mortality in three facilities in diverse resource settings in Kenya.

Setting: The study was conducted in three Kenyan hospitals.

Methods: We retrospectively analysed 1124 COVID-19 patient hospitalisation records (October 2020 – December 2021). Hypoxia was defined as the saturation of peripheral oxygen (SpO2) ≤ 94% at admission. Differences in categorical variables were assessed using the χ2 test. We used a multivariable Cox proportional hazards model to identify mortality predictors and Kaplan–Meier methods to estimate survival probabilities, with or without oxygen supplementation.

Results: Hypoxia was present in 81.4% of patients; 39.9% had no dyspnoea. Hypoxic patients compared to non-hypoxic patients were older (≥ 60 years: 44.6% vs. 24.4%) and had higher rates of dyspnoea (60.1% vs. 36.9%), hypertension (40.4% vs. 25.8%), and tachycardia (38.2% vs. 24.6%) (all p < 0.001). Only 68.6% of hypoxic patients received oxygen. Mortality was higher among hypoxic (38.0%) vs. non-hypoxic patients (13.6%, p < 0.001). Hypoxia independently predicted mortality (adjusted hazard ratio [aHR]: 1.9; 95% confidence interval [CI]: 1.2–2.8), particularly in older adults (aHR: 1.8) and those with dyspnoea (aHR: 1.5). Survival probabilities were worse for hypoxic patients regardless of dyspnoea or oxygen supplementation (p < 0.001).

Conclusion: Hypoxia was prevalent and significantly increased the mortality risk among hospitalised COVID-19 patients.

Contribution: Routine SpO2 monitoring and targeted hypoxia management are critical in low-resource settings, particularly for vulnerable patients.

Keywords: hypoxia; silent hypoxia; COVID-19-associated mortality; survival probabilities; Kenya.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic exposed critical weaknesses in healthcare systems worldwide, particularly in low-resource settings, where limited access to diagnostic and therapeutic tools posed significant challenges to effective patient management, resulting in widespread infections and mortality. By the end of December 2021, more than 282 million confirmed COVID-19 cases and over 5.4 million deaths had been officially reported globally.1 However, these numbers likely represent a substantial undercount since reporting systems were not optimal. Estimates of the global excess mortality suggest that the true death toll may have exceeded 14 million in the first 2 years of the pandemic, reflecting limitations in testing, reporting and vital registration systems, particularly in low- and middle-income countries.2 In Kenya, approximately 295 000 confirmed cases and 5378 deaths were reported by December 2021.3 However, national seroprevalence surveys and modelling studies suggest that actual infections and deaths were significantly higher than reported, because of limited testing capacity, healthcare access barriers and underreporting of community deaths.2,4,5,6 These figures underscore the urgent need for more effective triage and case management strategies in resource-constrained healthcare systems to reduce preventable mortality during such health crises.

Coronavirus disease 2019 mortality is driven by age, male sex, comorbidities (e.g., cardiovascular disease, diabetes) and markers of severe illness such as inflammation, respiratory failure and hypoxia. Among these, hypoxia – particularly ‘silent hypoxia’, where patients present with low saturation of peripheral oxygen (SpO2) without subjective symptoms like shortness of breath – has emerged as a powerful yet under-recognised predictor of mortality. Hypoxia, often overlooked during routine clinical evaluations, has been strongly linked to delayed intervention and increased mortality.7,8,9 Prior studies have shown that patients with ‘silent hypoxia’ exhibit alarmingly low SpO2 levels despite appearing clinically stable, leading to missed opportunities for timely intervention.10,11 For instance, while some studies have found no significant difference in outcome between silent and dyspnoeic hypoxia,12 others have reported higher risks of intensive care unit (ICU) admission or mechanical ventilation associated with silent hypoxia,13 underscoring how the deceptive presentation of silent hypoxia complicates triage – especially in overwhelmed or low-resource settings. Hypoxia is a hallmark of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, reflecting impaired gas exchange in the lungs and is associated with inflammatory responses, including the cytokine storm observed in critical cases.14,15 Multiple studies have confirmed that hypoxia correlates with COVID-19 severity, reinforcing its role as a key predictor of poor outcomes.16,17

Non-invasive pulse oximetry has emerged as an essential and cost-effective tool for early identification of hypoxia. By measuring SpO2, it provides vital information for guiding clinical decisions, such as hospitalisation and oxygen therapy.18 Normal SpO2 levels range from 95% to 100%, while values ≤ 94% are considered hypoxic according to clinical guidelines, including those used in Kenya.19,20 The World Health Organization (WHO) recommended the use of routine pulse oximetry in COVID-19 case management because of its simplicity, speed, low cost and non-invasiveness.21,22 Saturation of peripheral oxygen alone or in combination with the fraction of inspired oxygen (SpO2/FiO2) has proven valuable and economical for monitoring respiratory function over time in patients with COVID-19.23 However, in resource-constrained settings, the underutilisation of pulse oximetry – combined with limited oxygen supplies and staffing shortages – exacerbated challenges in recognising and managing hypoxia.24,25 Moreover, traditional diagnostic tools, such as chest X-rays, often failed to correlate with hypoxia, further complicating management.26 Patients with pre-existing chronic conditions – such as chronic obstructive pulmonary disease, cardiovascular disease or obesity – were particularly vulnerable to poor outcomes, highlighting the need for prompt SpO2 monitoring.27,28,29,30,31,32 These findings are consistent with a recent multicentre study that evaluated predictors and frequency of silent hypoxia in COVID-19 patients. The authors reported a silent hypoxia prevalence of approximately 30%, with silent hypoxia independently associated with increased ICU admissions and mechanical ventilation.13 Notably, this form of hypoxia often remained undetected without the aid of pulse oximetry, reinforcing the need for systematic SpO2 monitoring at admission, particularly in resource-limited settings where clinical signs alone may not reveal hypoxia.

We hypothesised that hypoxia at admission is an independent predictor of in-hospital mortality among COVID-19 patients. This study investigates the prevalence and clinical impact of silent hypoxia among COVID-19 patients admitted to three referral hospitals in Kenya. Analysing patient outcomes, our study underscores the critical role of SpO2 monitoring in reducing mortality and improving hypoxia management in resource-limited healthcare systems. In addition, we explored the availability of pulse oximetry, the prevalence of hypoxia and its association with mortality during the pandemic, offering actionable insights to address these challenges in similar settings.

Research methods and design

Study design and population

This retrospective cohort study was conducted in three purposively selected referral facilities in three counties: Mbagathi County Referral Hospital (Nairobi County), Jaramogi Oginga Odinga Teaching and Referral Hospital (Kisumu County), and Kilifi County Referral Hospital (Kilifi County). The purposive selection of the three facilities was conducted in collaboration with the Division of Integrated Disease Surveillance and Response (DDSR), Ministry of Health, and was based on the high number of COVID-19 cases reported during the selected study period and the prevalence of human immunodeficiency virus (HIV) in the three counties. Nairobi County has a reported HIV prevalence of 3.8%, Kisumu County 17.5%, and Kilifi County 2.3%33 As of the end of 2021, the cumulative COVID-19 caseload was 119 538 in Nairobi, 7368 in Kisumu and 6461 in Kilifi County.3

Epidemiological background

The first COVID-19 case in Kenya was reported on 13 March 2020. During the period covered by this study, Kenya underwent four distinct waves of SARS-CoV-2 infections, driven by different variants B.1 (2nd wave: October 2020 to January 2021), Alpha/Beta (3rd wave: February to May 2021), Delta (4th wave: June 2021 to November 2021), and Omicron (5th wave: December 2021) variants.34 As of 31 December 2021, Kenya had recorded 297 155 confirmed COVID-19 cases and 5381 deaths, resulting in a case-fatality rate of 1.8%.35

Data collection and abstraction procedures

The study involved a retrospective cohort analysis of inpatient medical records from hospitalised COVID-19 patients in Kenya spanning 01 October 2020 to 31 December 2021. A team of trained research assistants, comprising clinical and health records officers, enumerated all the inpatients with a diagnosis of COVID admitted to the three facilities in that time period. Medical charts for these patients were retrieved from the health records departments for abstraction. The data were accessed for research purposes at different times in each facility: Kilifi County Referral Hospital, 05 October 2022 to 19 October 2022; Jaramogi Oginga Odinga Teaching and Referral Hospital, 09 November 2022 to 02 December 2022; and Mbagathi County Referral Hospital, 09 February 2023 to 24 February 2023. Data were abstracted using a formatted data abstraction tool programmed in Open Data Kit (ODK), (https://opendatakit.org), and submitted to a central server for processing and analysis. All the data were stripped of all personally identifying information.

Operational definitions and measures

A case infected with SARS-CoV-2 was defined as a patient with a positive rapid diagnostic test or polymerase chain reaction (PCR) test result, or who was presumptively managed for COVID-19 based on symptomatic presentation, and was the dependent variable. Independent variables included clinical signs and symptoms, which were also abstracted, including fever, cough, and chest tightness. Chest X-ray findings (normal and abnormal), if available, were also abstracted. Comorbidities such as diabetes and hypertension were abstracted as present if the patient had reported them, even if blood glucose levels or current blood pressure readings were normal. We defined SpO2 as the proportion of haemoglobin bound to oxygen relative to the total haemoglobin available. Hypoxia was defined as SpO2 less than or equal to 94% on room air at admission.10 Fever was defined as elevated body temperature > 37.2 °C, and high respiratory rate (RR) as ≥ 30 breaths/minute. The outcome variable categories were in-hospital death, discharge or referral to another facility. Provision of supplemental oxygen was captured after admission, and dyspnoea was symptomatically assessed and documented as a presentation of the patients with respiratory distress or shortness of breath.

Analyses

We tested for the differences in distribution using the Pearson Chi-square (χ2) test. We assessed predictors for mortality for patients with hypoxia using Cox proportional hazards regression after calculating the time from admission to death in days and censoring the outcome. We included all potential predictors in the crude analyses after testing for the assumption of proportionality using the Schoenfield test, and included variables with a significance level of p < 0.1 in the univariate analysis step in the final multivariable model. In the multivariable model, we controlled for SpO2, age (in years), hypertension, diabetes, cardiovascular disease and dyspnoea. We additionally calculated survival probabilities by hypoxia status at admission for patients on room air and oxygen supplementation using the Kaplan-Meier method, and produced survival graphs by hypoxia status. We used Stata (ver.15) for statistical analysis and R for Cox proportional hazards regression analysis and to generate the survival curves. We considered statistical significance at p < 0.05.

Ethical considerations

This study was in accordance with relevant guidelines and regulations, having been reviewed by Centers for Disease Control and Prevention (CDC) and deemed not research, and was conducted, consistent with applicable federal law and CDC policy (45 C.F.R. part 46.102(l)(2), 21 C.F.R. part 56; 42 U.S.C. Sect. 241(d); 5 U.S.C. Sect. 552a; 44 U.S.C. Sect. 3501 et seq). Ethical clearance to conduct this study was obtained from the US Department of Health and Human Services, Centers for Disease Control and Prevention (CGH-KEN-7/26/22-90353), the Africa Medical Research Foundation (AMREF) Health Africa in Kenya’s Ethics and Scientific Review Committee (AMREF-ESRC P1233/2022), the University of California, San Francisco Human Research Protection Program Institutional Review Board (IRB: 22-37353), Jaramogi Oginga Odinga Teaching and Referral Hospital (REF: ISERC/JOOTRH/638/22), and Kilifi County Referral Hospital (REF: COH/DOH/RESEARCH/VOL.2/174). All three participating hospitals provided institutional approvals. The Kenya National Commission for Science, Technology, and Innovation (NACOSTI) additionally permitted this study (Licence No: NACOSTI/P/22/19903). Because of the study’s retrospective nature and the use of de-identified data, the requirement for individual patient consent was waived.

Results

Socio-demographic and clinical characteristics

Among 1124 patients hospitalised with COVID-19, 1066 (94.8%) had documented SpO2 measurements at admission, of whom 868 (81.4%) had hypoxia. Hypoxic patients compared to those with normal SpO2 levels were significantly older (60+ years: 44.6 vs. 24.4%) and had a higher prevalence of dyspnoea (60.1% vs. 36.9%), higher pulse rate (38.2% vs. 24.6%), and hypertension (40.4% vs. 25.8%) (p < 0.001). Among patients with hypoxia, about 2 in every 5, 346 (39.9%) did not have dyspnoea p < 0.001. A higher proportion of patients with hypoxia died compared to those with normal SpO2 (38.0% vs. 13.6%) p < 0.001 (Table 1).

TABLE 1: Patients’ demographic and clinical characteristics by hypoxia and mortality, Kenya 2020–2021.
Dyspnoea and coronavirus disease 2019 outcomes

Among all COVID-19 patients without dyspnoea, hypoxic patients had threefold more deaths than those with normal SpO2 (29.8% vs. 9.6%), p < 0.001. Among all COVID-19 patients with dyspnoea, hypoxic patients had twofold more deaths than those with normal SpO2 (43.5% vs. 20.6%), p = 0.002 (Figure 1).

FIGURE 1: Hypoxia and outcomes for coronavirus disease 2019 patients with and without dyspnoea, Kenya 2020–2021.

Among all COVID-19 patients, those with hypoxia had a higher proportion of deaths than those with normal SpO2 (38.0% vs. 13.6%), p < 0.001. There were more deaths among COVID-19 patients with hypertension and hypoxia compared to hypertensive patients with normal SpO2 (42.5% vs. 7.8%), p < 0.001. For COVID-19 patients without hypertension, mortality was higher among patients who had hypoxia (35.0%) compared to patients with normal SpO2 (15.6%), p < 0.001 (Figure 2).

FIGURE 2: Hypoxia and mortality for all patients with and without hypertension, Kenya 2020–2021.

Predictors of coronavirus disease 2019 mortality

Whether on oxygen supplementation or room air, survival probabilities were better for patients who did not have hypoxia on admission. Survival for non-hypoxic COVID-19 patients on room air plateaued from about 2 weeks of hospitalisation, while survival for hypoxic patients continued to worsen at a more rapid pace (Figure 3). Both hypoxic and non-hypoxic patients had similar declining survival rates beyond a month of hospitalisation. Half of the hypoxic patients on room air survived up to the 20th day, and over half of the non-hypoxic patients on room air survived over the 50th day. For patients on supplemental oxygen (Figure 3), survival probabilities rapidly worsened, and by around 10 days, over half of the hypoxic patients on admission were dead, compared to non-hypoxic patients on admission who survived a little longer.

FIGURE 3: Survival probabilities for coronavirus disease 2019 patients (a) on room air and (b) on oxygen supplementation, by saturation of peripheral oxygen levels, Kenya 2020–2021.

Out of 1123 patients admitted with COVID-19, 1122 recorded time-to-outcome data, and 868 experienced hypoxia. The median duration of admission was 6 days, with interquartile range (IQR) 2–10. Among the 1066 patients with hypoxia data, 357 (33.5%) died. Mortality was significantly higher in hypoxic patients (38.0%) compared to those with normal oxygen levels (13.6%) (p < 0.001). Lower mortality rates were observed in non-hypoxic patients, females, those under 40, those with formal employment, HIV negative individuals, and those without hypertension, diabetes, cardiovascular issues or dyspnoea. Crude proportional hazards analysis identified hypoxia, age, hypertension, diabetes, cardiovascular issues and dyspnoea as significant factors affecting survival (p < 0.05). In the adjusted model, hypoxia (adjusted hazard ratio [aHR] = 1.9 [95% confidence interval {CI}:1.2–2.8]), older age (≥ 60 years; aHR = 1.8 [95% CI:1.3–2.6]) and dyspnoea (aHR = 1.5 [95% CI: 1.2–2.0]) were associated with a higher risk of death (Table 2).

TABLE 2: Predictors of mortality in hospitalised coronavirus disease 2019 patients with hypoxia, Kenya 2020–2021.

Discussion

This study highlights the critical role of hypoxia in determining the outcomes of patients hospitalised with COVID-19. We found that approximately 8 out of 10 patients hospitalised with COVID-19 had hypoxia (SpO2 ≤ 94%) at admission, a condition that was associated with significantly higher mortality rates compared to those with normal SpO2. The prevalence of hypoxia was particularly higher among older patients and those with clinical symptoms consistent with COVID-19, such as cough, chest tightness, low pulse rate, dyspnoea, and underlying comorbidities like hypertension and HIV infection. This relationship suggests that symptomatic COVID-19 disease may have a consistent prognosis even in the absence of diagnostic testing, a finding supported by similar studies.36 Notably, about 40% of our patients experienced silent hypoxia, a proportion that aligns with estimates from other studies, which range between 4.8% and 65%.36 This high burden of hypoxia upon admission emphasises the need to evaluate its prognostic significance, particularly its relationship with mortality and survival outcomes among hospitalised patients.

SpO2 has emerged as a crucial predictor of survival in COVID-19 patients.27 Mortality among hypoxic patients was 38.0%, nearly threefold that of non-hypoxic patients (13.6%). This is consistent with literature indicating that hypoxia is a key predictor of poor prognosis in respiratory infections.27,28,37 Moreover, older hypoxic patients had twice the risk of death compared with patients under 40, which is consistent with global findings.38 While hypertension was not independently associated with mortality in our study, it is generally recognised as a risk factor for severe COVID-19 and poor outcomes.39 Our findings suggest that normal SpO2 levels are associated with better survival probabilities, while hypoxia, along with age and dyspnoea, independently predicts a higher risk of death. Therefore, oxygen supplementation is essential for hypoxic patients, as studies have shown that higher SpO2 levels after supplementation are linked to reduced mortality,36 and improved survival probabilities.28 The observation that patients with hypoxia had over three times the mortality rate underscores the importance of assessing SpO2 in all COVID-19 patients, regardless of their symptomatic presentation.

Oxygen supplementation is recommended for hypoxic patients. Although oxygen supplementation is a cornerstone of COVID-19 management, our study’s observational design limits causal inference regarding its impact on survival. While hypoxic patients who received oxygen had lower survival probabilities – likely reflecting underlying disease severity rather than the effect of oxygen itself – this should not be interpreted as evidence that oxygen provision is ineffective. Instead, our findings highlight the urgent need for timely and equitable access to oxygen in line with global recommendations. Studies elsewhere have shown that when administered early, oxygen therapy improves survival outcomes in hypoxic patients.27,35 Thus, our results reinforce the global consensus on the importance of oxygen access, while recognising that real-world outcomes in resource-constrained settings may be influenced by multiple co-occurring factors such as delayed presentation, limited monitoring or inadequate dosing strategies. It is important to note that only 3 out of 5 (68.6%) of hypoxic patients in our study received oxygen supplementation, reflecting gaps in care delivery. The national guidelines recommend oxygen supplementation for patients with SpO2 ≤ 94%. While this threshold was the standard at the time, emerging evidence has since suggested that stricter thresholds (e.g., < 92%) might improve early detection of deterioration and might have been beneficial.40 We also lacked data on whether follow-up SpO2 readings were taken after initial drops by 3% – 5%, which is a recommended practice, as has been suggested by Galwankar et al.41 Community-level SpO2 monitoring, such as providing oximeters to households,42 could be beneficial for ongoing patient management post-discharge, though we did not follow patients after discharge.

Our study had some limitations. We lacked COVID-19 diagnostic information for some cases, relying instead on clinician documentation based on symptomatic presentation. Additionally, SpO2 data were missing for 5.2% of records, but this low proportion is unlikely to bias our findings. The relatively stringent definition of hypoxia used in this study may have led to the misclassification of some patients as having silent hypoxia, though we adhered to national guidelines. The prevalence of hypoxia in this study was higher than in many global settings. However, our purposive selection of high-volume referral hospitals likely captured a sicker population and may have inflated these estimates. This selection bias, along with the retrospective nature of the study and variability in documentation, limits generalisability to the broader Kenyan context, including patients with milder disease managed in lower-level facilities. Furthermore, retrospective data reviews are prone to missing information, inconsistent clinical documentation and recall bias, all of which may affect data accuracy. To mitigate these issues, we made concerted efforts to verify patient chart contents and collaborated closely with facility health records officers to enhance data quality. A key limitation is that the association between hypoxia and mortality may be confounded by treatment gaps, as not all hypoxic patients received oxygen, making the hazard ratio reflect both disease severity and inadequate management in a low-resource setting. We also did not track patient outcomes of COVID-19 patients post-discharge. Finally, we could not determine whether hypertensive patients had a history of hypertension or elevated blood pressure before admission. Despite these limitations, our study provides valuable insights into the utility of SpO2 monitoring for the clinical management of hospitalised COVID-19 patients.

Conclusion

Our findings suggest that SpO2 monitoring is essential in managing hospitalised COVID-19 patients, especially in low-resource settings. While comorbidities may play a role in disease progression, hypoxia and age were the strongest independent predictors of mortality in our cohort. Importantly, the frequent occurrence of silent hypoxia supports its inclusion in triage protocols. Our findings highlight critical patterns in clinical presentation and outcomes that are likely relevant to similarly resourced public facilities across Kenya. Nonetheless, we caution against extrapolating these findings to rural or private settings without further investigation and recommend future studies with broader facility representation. Future research should directly model silent hypoxia as a primary exposure variable to better quantify its independent association with mortality. In addition, studies that incorporate broader severity indicators and follow-up outcomes will be vital in refining clinical care strategies for similar low-resource settings.

Acknowledgements

We thank the Kenyan Ministry of Health, the Division of Disease Surveillance and Response (DDSR), the National AIDs and STIs Control Programme (NASCOP), viral load testing laboratories, implementing partners and patients. This work was supported by the President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC). A preprint version of this work (Hypoxia as a predictor of mortality among patients admitted with COVID-19 disease in three referral hospitals in Kenya, October 2020 to December 2021) was previously published on www.medrxiv.org https://doi.org/10.1101/2024.10.17.24315667,43 and we acknowledge its role in shaping the final manuscript.

Competing interests

The authors of this publication reveived research funding from the American Rescue Plan Act of 2021 and the US President’s Emergency Plan for AIDS Relief (PEPFAR) through cooperative agreements (GH002338, GH002266, & GH002339) from the US Centers for Disease Control and Prevention (CDC), Division of Global HIV & TB (DGHT) which is developing products related to the research described in this publication. In addition, the author serves as a consultant to the entity and received compensation for these services. The terms of this arrangement have been reviewed and approved by the CDC in accordance with its policy on objectivity in research.

Authors’ contributions

A.W. conceptualised the manuscript, analysed the data and drafted the initial and subsequent drafts of the manuscript. J.M.W. contributed to the analyses. F.O. assisted in data collection and cleaning. M.M., P.M., W.W., S.J., A.N., D.O., and N.M. contributed substantially to protocol development, data collection and critical review of the manuscript. C.N., A.M. and J.O. provided administrative approvals, including study processes. All authors read and approved the final version of the manuscript.

Funding information

This publication was made possible by support from the American Rescue Plan Act of 2021 and the US President’s Emergency Plan for AIDS Relief (PEPFAR) through cooperative agreements (GH002338, GH002266, & GH002339) from the US Centers for Disease Control and Prevention (CDC), Division of Global HIV &TB (DGHT).

Data availability

Data sharing is not applicable to this article, as no new data were created or analysed in this study.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

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