Integrating SARS-CoV-2 rapid antigen testing in maternal, neonatal and child health, HIV and tuberculosis services in Cameroon and Kenya: a cluster randomised trial of two testing models

Abstract

Introduction

Identifying SARS-CoV-2 infection in high-risk populations is critical. We examined SARS-CoV-2 case detection (CD) in ‘TA’ versus ‘screen-and-test’ models of rapid antigen testing integration in maternal neonatal and child health (MNCH), HIV and tuberculosis (TB) clinics in Cameroon (C) and Kenya (K).

Methods

From May to October 2022, we conducted a cluster-randomised trial with 10 facilities per country randomised to the ‘test-all’ (TA) intervention arm or the standard ‘screen-and-test’ (ST) arm. Individuals aged >2 years attending HIV, TB and MNCH clinics were eligible for SARS-CoV-2 testing. The primary outcome was the SARS-CoV-2 CD, defined as the number of SARS-CoV-2 infections detected per 1 000 attendees in MNCH, HIV and TB clinics. We estimated the intervention arm-specific CDs by combining the facility-specific estimates using a weighted approach.

Results

There were 80 828 attendee visits in the TA model (63 492 C, 17 336 K) and 71 254 in the ST model (56 589 C, 14 665 K). About 17.4% (K) and 29.0% (C) were tested under the TA model. The overall CD was 2.90 (95% CI:1.76 to 4.79) per 1 000 attendee visits in the TA model and 1.20 (95% CI:0.73 to 1.99) in the ST model (RR=2.41, 95% CI:1.18 to 4.91, p=0.018). The TA model had a significantly higher SARS-CoV-2 CD in MNCH clinics (2.91 vs 1.11, p=0.012), while CD estimates in HIV (2.88 vs 1.40, p=0.203) and TB (10.24 vs 4.57, p=0.051) clinics, although higher in TA model compared with ST model, were not statistically different.

Conclusions

The TA model identified more SARS-CoV-2 cases than the screen-and-test model, even with low testing coverage. The TA model could be considered in future epidemics for early detection of SARS-CoV-2 infection among vulnerable populations, but effective implementation requires additional human resources to manage testing in high volume clinics.

Trial registration number

NCT05382130.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• In response to the rapid spread of SARS-CoV-2, the WHO declared the COVID-19 disease a global pandemic in 2020 and approved the use of antigen rapid detection tests (Ag-RDTs) to detect COVID-19 cases.

• Most national COVID-19 response programmes used a screen-and-test strategy to identify infection among symptomatic individuals and those at risk due to exposure because of the limited availability and costs of broader testing.

• Our search captured literature on SARS-CoV-2 transmissions among asymptomatic cases and the role of Ag-RDTs in prevention and control of infection across the communities.

WHAT THIS STUDY ADDS

• This study adds new evidence on two SARS-CoV-2 Ag-RDT integration testing models, test-all and screen-and-test, for clinic attendees across HIV, tuberculosis (TB) and maternal neonatal and child health (MNCH) clinics entry points. Data on the feasibility of this integration was unavailable in the African context, including in Kenya and Cameroon.

• Our study found that integration of the test-all model was more effective in the identification of asymptomatic SARS-CoV-2 cases. Our study also revealed that compared with the screen-and-test model, there was a significantly higher SARS-CoV-2 case detection in the test-all strategy in MNCH clinics. Though overall case detection was higher in TB and HIV clinics than in MNCH clinics in both models of integration, there was no significant difference between the models.

• Integration of SARS-CoV-2 Ag-RDTs using the test-all model is effective at identifying more SARS-CoV-2 cases during a global pandemic in vulnerable populations such as MNCH, HIV and TB clinic clients in Kenya and Cameroon.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• The findings of this study provide new evidence on the models of integration of Ag-RDTs for identification of SARS-CoV-2 cases in the health system.

• The data can be used to guide the implementation of the test-all integration model for future SARS-CoV-2 pandemic response programmes.

• Uptake of the test-all integration model could be considered in future epidemics, but will require additional considerations such as staffing, demand creation, community sensitisation and procurement of commodities for effective implementation.

Introduction

When the SARS-CoV-2 pandemic emerged as a global threat, its rapid spread across sub-Saharan Africa called for an urgent response. At its peak around December 2021, Kenya reported one of the highest numbers of COVID-19 cases in East Africa with over 250 000 confirmed cases and over 5 300 deaths.^{1 2} Similarly, in Central Africa, Cameroon had the highest recorded cases in the region, reporting over 109 000 confirmed cases and over 1 800 deaths.^{2 3} The COVID-19 pandemic increased the burden on pre-existing fragile health systems in low- and middle-income countries, with higher impacts on vulnerable populations.

SARS-CoV-2 infection is associated with more severe outcomes, including higher morbidity and mortality, in immunocompromised populations including pregnant women, people living with HIV (PLHIV) and individuals with tuberculosis (TB) infection.4,7 Pregnant women are at higher risk for exacerbated COVID-19 symptoms and poorer pregnancy outcomes. Multiple studies have reported a higher risk of pregnancy complications, including preterm birth and preeclampsia, as well as higher rates of caesarean deliveries in pregnant women with SARS-CoV-2.^{8 9} It was also reported that slightly more than 25% of pregnant patients were asymptomatic at diagnosis.⁸ Meta-analyses conducted by Wang et al and Sarkar et al concluded that patients with both TB and COVID-19 had an increased risk for disease severity and mortality compared with those without TB.^{4 5} Increased risk for severe COVID-19 disease progression (hospitalisation and/or death) was also reported in patients with HIV, even those with well-controlled HIV infection.¹⁰ Bertagnolio et al found that PLHIV have 15% higher odds of being admitted to the hospital with severe or critical SARS-CoV-2 and 38% higher odds of developing fatal COVID-19 compared with those without HIV infection.¹¹

Similarly, young children pose a unique challenge for this pandemic. The majority of children infected with the SARS-CoV-2 virus are asymptomatic or present with mild symptoms and, therefore, are less likely to be tested or isolated. A study evaluating children and adolescents from ages 0 to 17 years found overall transmission of SARS-CoV-2 occurred in 27% of households.¹² Children under 3 years of age showed the highest odds of transmitting SARS-CoV-2 to household contacts. There is a critical need to increase access to testing and early diagnosis for SARS-CoV-2 infection to reduce viral spread and improve health outcomes, especially among higher risk populations.

Performing SARS-CoV-2 antigen rapid detection tests (Ag-RDTs) in at-risk populations has the potential to identify infected individuals early with prompt referral for care, initiation of treatment and quarantine. Asymptomatic mass testing programmes, such as the ‘test-all (TA)’ strategy, facilitate early case identification, especially in high-prevalence settings.^{13 14} The potential for asymptomatic transmission of SARS-CoV-2 is well recognised, leading to delayed isolation of carriers and worldwide spread.^{15 16} In multiple studies conducted in the USA and China, asymptomatic infections comprised more than 50% of positive cases.17,19 The high proportion of transmission events derived from asymptomatic or presymptomatic infections makes SARS-CoV-2 difficult to control through the traditional, ‘screen-and-test (ST)’ symptom-based testing, isolation and contact tracing.²⁰

Identification of asymptomatic carriers of SARS-CoV-2 is important in the mitigation of the pandemic.^{21 22} This study aimed to determine the effectiveness of a TA model of SARS-CoV-2 testing integration in maternal neonatal and child health (MNCH), HIV and TB clinics in Kenya and Cameroon compared with testing integration with the standard ST model as measured by the SARS-CoV-2 case detection (CD) defined as the number of SARS-CoV-2 infections detected per 1000 clinic attendees. The study also aimed to evaluate the effect of the TA model on testing of contacts.

Methods

Study design and setting

We conducted a pragmatic cluster-randomised trial with health facilities (clusters) randomised to the SARS-CoV-2 TA model (intervention) or to the ST model (control) in Kenya and Cameroon. The study was conducted in a subset of health facilities participating in the Elizabeth Glaser Pediatric AIDS Foundation ‘Catalyzing COVID-19 Action’ (CCA) Project. This project integrated SARS-CoV-2 Ag-RDTs into routine services in three clinics (MNCH, HIV and TB) in 60 health facilities in Cameroon and Kenya (30 per country) purposively selected by the Ministries of Health (MOHs) to include different health system levels (primary, secondary and tertiary) and geographic settings (urban, semiurban and rural). The CCA Project was conducted in Kiambu County in Kenya and the Central, Littoral and Western regions of Cameroon.

Study site selection

10 facilities in each country were selected from the CCA Project facilities based on clinic patient volumes that would allow for feasible SARS-CoV-2 testing of all clinic attendees. CCA facilities were sorted by increasing patient volume, and the 10 facilities with the lowest patient volumes were selected to be included in the study. These facilities were randomised to TA (testing offered regardless of screening outcome) or ST (testing offered if screened positive) models in equal numbers using a computer-generated random sequence in a 1:1 ratio.

Study population and procedures

All individuals aged >2 years attending MNCH, HIV and TB clinics between May 2022 and October 2022 were included. In the ST model, SARS-CoV-2 infection screening questions were administered to all clinic attendees, followed by SARS-CoV-2 Ag-RDTs testing offered only to attendees that met testing eligibility requirements based on the country guidelines. In both countries, the screening questions included a review of the COVID-19 clinical symptoms and history of exposure to someone with SARS-CoV-2 infection. In the TA model, SARS-CoV-2 infection screening questions were administered to all clinic attendees, followed by SARS-CoV-2 Ag-RDT testing offered to all attendees irrespective of the screening results. Demographic, screening and testing information on all clinic attendees (including individuals accompanying them) was captured through dedicated paper forms in Cameroon or an electronic medical record interface in Kenya. Deidentified data for all attendees in the study clinics during the study period were extracted from the SARS-CoV-2 programme data into the study database for analysis. All clinic attendees in the selected study clinics seen during the study period were included in the study population for comparison of TA and ST models.

Additional staff were hired to support the implementation of the SARS-CoV-2 testing in both countries. In Kenya, community health volunteers and laboratory technicians were hired to conduct the screening and testing activities, respectively, in both models of integration. In Cameroon, the screening and testing for SARS-CoV-2 was integrated as part of the routine service delivery in all health facilities and provided by the existing health facility staff. However, additional testing agents were hired to support the increased testing for SARS-CoV-2 in TA facilities only. Sample collection and testing were conducted by trained personnel using MOH-approved SARS-CoV-2 Ag-RDTs, Abbott Panbio or SD Biosensor Standard Q, according to the MOH and manufacturers guidelines and procedures with appropriate personal protective equipment. The testing algorithms in both Cameroon and Kenya included SARS-CoV-2 PCR testing only for those who were symptomatic with COVID-19-like symptoms or those who were high-risk close contacts and tested negative on the Ag-RDTs. The samples were processed by trained personnel within the study facilities, adhering to national infection prevention and control guidelines recommended by the MOH in both countries.

Screening and testing results were provided to attendees with appropriate counselling and recorded in the standard clinic COVID-19 forms in Cameroon and the electronic system in Kenya by health facility staff. Repeat testing was available to those who returned to the routine care more than once in the same clinic or different clinics (MNCH, HIV or TB), with the condition that their previous test was conducted two or more weeks prior to the visit. The clinical management of SARS-CoV-2 positive cases was based on the case severity, following MOH guidelines in Cameroon and Kenya. Based on the national guidelines, severe cases were admitted to hospitals and provided with oxygen and medical treatment, while moderate, mild and asymptomatic cases were managed with home-based care and advised to monitor the worsening of signs and symptoms related to COVID-19 while in isolation. The informed consent or assent for sample collection was not directly obtained from study participants; instead, the study adhered to standard SARS-CoV-2 screening and testing procedures as established by the national guidelines. In the TA facilities, information about the facility’s provision of SARS-CoV-2 testing to all clinic attendees was posted in appropriate languages in several locations in each clinic. This included notification that attendees may choose to opt out of the SARS-CoV-2 testing. In the protocol, the plan was to provide participants with a SARS-CoV-2 positive test, a coded contact form and testing forms to their main close contacts, but this was not implemented for all patients across all sites.

Sample size, power and effect size considerations

Sample size considerations were based on the primary objective to estimate the effectiveness of the ‘TA’ strategy on the proportion of patients diagnosed with SARS-CoV-2 infection compared with the screen and test strategy following SARS-CoV-2 Ag-RDT integration in MNCH, HIV and TB clinics. Based on data from Cameroon, the CD among all clinic attendees under the ‘ST’ was 1 case per 100 attendees (1%). Assuming 6000 clinic attendees would be observed per arm in each country, we estimated the minimum detectable effect in COVID-19 CDs (and expected relative ratios) under different design effect sizes (to account for potential clustering of COVID-19 cases) and different CD under ST with 80% power at 5% significance level. Under these assumptions, we estimated that we would have power to detect a minimum relative increase in CD ranging from 29% to 63%.

Statistical analysis

Statistical analyses were performed separately by country due to the varying nature of the epidemics and because the study was powered per each individual country. The primary outcome was SARS-CoV-2 CD defined as the number of SARS-CoV-2 infections detected per 1000 attendees in MNCH, HIV and TB clinics. The outcomes along the testing cascade were also determined from attendance through screening, testing and results per country and per clinic. We summarised participants’ demographic characteristics using frequencies and proportions for categorical variables stratified by the model. We estimated the proportion of attendees screened, tested and SARS-CoV-2-positive by study arm. The SARS-CoV-2 CD was estimated for each health facility by the number of clinic attendees diagnosed with SARS-CoV-2 infection divided by the total number of clinic attendees at MNCH, HIV and TB clinics multiplied by 1000. We estimated the intervention arm-specific CD by combining the facility-specific estimates using a weighted approach. First, we log-transformed the cluster-specific proportions which we estimated by adding 0.5 cases and 0.5 patients to the numerator and denominator to account for clusters with no COVID-19 cases. To account for inefficiencies that arise from different cluster sizes, we estimated inverse-variance weights of the log-proportions (23). We used a weighted t-test to compare CDs between the two study arms. We also present unweighted cluster-level analyses as a sensitivity analysis on the influence of the weights (since they are also estimated). Statistical analyses were performed using R software (V.4.4.0; R Core Team, 2024. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org) and Rstudio (version 2024.04.1, RStudio Team, 2024. RStudio: Integrated Development for R. RStudio, PBC, Boston, Massachusetts, USA. URL http://www.rstudio.com/).

Patient and public involvement

Patients or the public were not involved in the design, conduct, reporting or dissemination plans of our research.

Results

Overall, 152 082 attendee visits were reported during the study period in Kenya and Cameroon. A total of 71 254 (46.9%) were reported in the ST model and 80 828 (53.1%) attendee visits were reported in the TA model (figure 1). Screening for SARS-CoV-2 was performed in 48 314 (67.8%) of attendees in the ST arm compared with 42 325 (52.4%) of attendees in the TA arm. Among those who were screened for SARS-CoV-2 in the ST model, 3629 (7.5%) were eligible for SARS-CoV-2 testing, of which 2 139 (58.9% of eligible attendees) were tested, with 88 cases identified (4.1%). A total of 21 536 attendees (26.6% of all attendees) in the TA model were tested for SARS-CoV-2, with 312 cases identified (1.4%). Overall, 400 SARS-CoV-2 infections were identified, with the majority found in Cameroon (345 cases) compared with Kenya (55 cases).

Figure 1. SARS-CoV-2 testing cascade for the two integration models overall and by country.

Results of the screening and testing cascade differed by country (figure 1). In Cameroon, 56 589 attendee visits were reported in the ST facilities. Of these, 41 190 (72.8%) were screened, and 3362 (8.2%) were eligible for SARS-CoV-2 testing, of whom 1919 (57.1%) were tested with 66 cases identified (3.4%). In the TA model, 29.0% (18 526/63 492) of all attendees were tested for SARS-CoV-2 with 279 cases identified (2%). In Kenya, a total of 14 665 and 17 336 attendees were seen in the ST and TA models, respectively. In the ST model, 7124 (48.6%) were screened for COVID-19 symptoms/exposure, 267 (3.7%) were eligible for testing and 220 (82.4%) were tested with 22 cases identified (10%). In the TA model, 3010 (17.4%) clinic attendees were tested for SARS-CoV-2, with 33 cases identified (1.1%).

Overall, the average cluster adjusted CD was 1.20 (95% CI: 0·73 to 1.99) per 1 000 attendee visits in the ST model compared with 2.90 (95% CI: 1.76 to 4.79) per 1 000 attendee visits in the TA model. The probability of detecting SARS-CoV-2 using the TA model was over twice that of the ST model (relative risk (RR)=2.41, 95% CI: 1.18 to 4.91, p=0.018) (table 1). In Cameroon, the CD was significantly higher (RR=3.70, 95% CI: 1.66 to 8.26, p=0.006) in the TA health facilities (CD=4.34, 95% CI: 2.46 to 7.65) compared with the ST health facilities (CD=1.18, 95% CI: 0.67 to 2.08). However, in Kenya, there were no significant differences (RR=1.52, 95% CI: 0.42 to 5.51, p=0.474) in CD between the TA model (1.86, 95% CI: 0.76 to 4.58) and the ST model (1.23, 95% CI: 0.49 to 3.07) (see online supplemental table 1).

Table 1. SARS-CoV-2 case detection in each health facility by model, overall and by country.

	Screen-and-test (n=10 facilities)			Test-all (n=10 facilities)			Effect
Cluster (facility)	Total (N)	Positive	Cases per 1000 attendees (95% CI)	Total (N)	Positive	Cases per 1000 attendees (95% CI)	Case detection ratio (95% CI)	P value
Overall
Overall totals	71 252	88	1.24 (0.99 to 1.52)	80 828	312	3.86 (3.44 to 4.31)	3.12 (2.48 to 3.98)	<0.001
Unweighted mean			1.22 (0.73 to 2.04)			2.86 (1.70 to 4.79)	2.35 (1.13 to 4.87)	0.025
Weighted mean			1.20 (0.73 to 1.99)			2.90 (1.76 to 4.79)	2.41 (1.18 to 4.91)	0.018
Cameroon facilities
Overall	56 589	66	1.17 (0.90 to 1.48)	63 492	279	4.39 (3.89 to 4.94)	3.77 (3.34 to 4.24)	<0.001
Unweighted mean			1.18 (0.67 to 2.08)			4.39 (2.49 to 7.73)	3.73 (1.67 to 8.35)	0.005
Weighted mean			1.18 (0.67 to 2.08)			4.34 (2.46 to 7.65)	3.70 (1.66 to 8.26)	0.006
Kenya facilities
Overall	14 665	22	1.50 (0.94 to 2.27)	17 336	33	1.90 (1.31 to 2.67)	1.27 (0.87 to 1.78)	0.169
Unweighted mean			1.26 (0.49 to 3.21)			1.86 (0.73 to 4.75)	1.48 (0.39 to 5.60)	0.514
Weighted mean			1.23 (0.49 to 3.07)			1.86 (0.76 to 4.58)	1.52 (0.42 to 5.51)	0.474

Data are presented as No.

Overall, CDs were significantly higher in TA facilities compared to ST facilities in MNCH clinics (RR =2.64, 95% CI: 1.27 to 5.48, p=0.012) and TB clinics (RR =2.25, 95% CI: 0.99 to 5.10, p=0.051) (table 2). In Cameroon, the TA model had a significantly higher SARS-CoV-2 CD compared to the ST model in MNCH clinics (RR =5.25, 95% CI: 2.72 to 10.13) and TB clinics (RR =2.50, 95% CI: 1.00 to 6.24) but not in HIV clinics (RR =1.98, 95% CI: 0.28 to 13.88). In Kenya, there were no significant differences in SARS-CoV-2 CDs between ST and TA models in MNCH (RR =1.27, 95% CI: 0.35 to 4.60), HIV (RR =2.08, 95% CI: 0.35 to 12.24) and TB (not estimable) clinics.

CD, case detection; MNCH, maternal neonatal and child health; RR, relative risk; ST, screen-and-test; TA, test-all; TB, tuberculosis.

Table 2. SARS-CoV-2 case detection by model and type of clinic by country.

	Screen-and-test (n=10 facilities)			Test-all (n=10 facilities)
	Attendees	Positives	Cases per 1000 attendees (95% CI)	Attendees	Positives	Cases per 1000 attendees (95% CI)	Case detection ratio (95% CI)	P value
Cameroon facilities
MNCH
Totals	30 005	27	0.90 (0.59 to 1.31)	38 712	181	4.68 (4.02 to 5.41)	5.20 (4.46 to 6.01)	<0.001
Weighted mean			0.93 (0.59 to 1.48)			4.89 (3.08 to 7.75)	5.25 (2.72 to 10.13)	<0.001
HIV clinic
Totals	25 508	33	1.29 (0.89 to 1.82)	23 229	79	3.40 (2.69 to 4.24)	2.63 (2.08 to 3.28)	<0.001
Weighted mean			1.16 (0.29 to 4.56)			2.29 (0.58 to 9.02)	1.98 (0.28 to 13.88)	0.443
TB clinic
Totals	1 076	6	5.58 (2.05 to 12.10)	1551	19	12.25 (7.39 to 19.06)	2.20 (1.32 to 3.44)	0.002
Weighted mean			5.40 (2.82 to 10.31)			13.41 (7.11 to 25.14)	2.50 (1.00 to 6.24)	0.049
Kenya facilities
MNCH
Totals	10 409	16	1.54 (0.88 to 2.50)	13 441	22	1.64 (1.03 to 2.48)	1.06 (0.67 to 1.61)	0.740
Weighted mean			1.32 (0.52 to 3.32)			1.66 (0.68 to 4.08)	1.27 (0.35 to 4.60)	0.684
HIV clinic
Totals	3 612	6	1.66 (0.61 to 3.61)	3488	10	2.87 (1.38 to 5.27)	1.72 (0.83 to 3.18)	0.091
Weighted mean			1.86 (0.50 to 6.83)			3.86 (1.17 to 12.66)	2.08 (0.35 to 12.24)	0.361
TB clinic
Totals	644	0	0 (0 to 5.74)	437	1	2.29 (0.06 to 12.68)	–
Weighted mean			0			2.71 (0 to 10.97)	–

Data are presented as No.

MNCH, maternal neonatal and child health; TB, tuberculosis.

Discussion

We found that integrating SARS-CoV-2 rapid antigen testing in MNCH, HIV and TB clinics using a TA model identified more SARS-CoV-2 cases and resulted in a higher CD than the standard ST model. This was most evident in Cameroon and in MNCH clinics, compared with Kenya or HIV and TB clinics, respectively. Despite less than a third of attendees being reached with testing in the TA model, 10 times more attendees were tested and almost four times more attendees were found to be positive for SARS-CoV-2 compared with the ST model. The notable success in Cameroonian health facilities could have been due to the stage of the COVID-19 epidemic at the time of the study, as well as the large sample size that provided enough power to detect the intervention effects.

The increased identification of SARS-CoV-2 infections in these high-risk populations in the TA arm is critical, given that there is considerable transmission from asymptomatic and presymptomatic individuals. The average time from exposure to symptom onset is 5 days, with up to 62% of transmissions prior to the onset of symptoms.²³ In other settings where transmission would be particularly problematic (hospitals, nursing homes and college campuses), several studies and models indicate that symptom-based screening alone would not be enough to control SARS-CoV-2 spread.24,26 The effectiveness of universal (TA) screening, however, is dependent on the frequency of testing, the rapid availability of test results, testing sensitivity and immediate response to positive results.^{25 26} The use of SARS-CoV-2 Ag-RDTs as in our study allows for cheaper and faster testing than the gold standard of PCR testing, though it has been found to have less sensitivity in different populations and circulating variants. Sensitivities when testing all with SARS-CoV-2 Ag-RDTs have ranged from 83.3% in hospitalised paediatric patients,²⁷ to 55% in asymptomatic women admitted for delivery²⁸ and to 31.8% in asymptomatic caregivers of patients in Korea.²⁹ However, all the cases identified would have been missed had there been only symptom screening-based testing.

We found considerable variability in how the SARS-CoV-2 testing models were implemented in each country. In Cameroon, screening and testing relied mostly on existing health facility staff who were providing care and treatment services. Given the increased workload and documentation demand in TA facilities, testing agents were hired to support the added SARS-CoV-2 testing. Kenya implemented a different approach with specific staff hired to support the screening and testing of SARS-CoV-2 in all health facilities in both arms, thus not relying on existing health facility staff. Use of existing staff led to a higher proportion of attendees screened (ST arm) and tested (TA arm) in Cameroon than Kenya. Also, the health staff capacity for ST or TA was more effective in entry points with low patient volumes, such as the TB clinic. This is consistent with Wee et al who studied the use of SARS-CoV-2 Ag-RDTs for testing all asymptomatic hospital visitors and found that it was logistically challenging to perform in high volume facilities such that they had to limit testing to only visitors staying for longer than 30 min to manage the volume.³⁰ They also found that it was resource-intensive and low yield in low incidence settings. However, the yield increased during pandemic waves, indicating that there may be a specific role of more value at those times. Wee et al also found higher yield with Ag-RDTs for all patients in their emergency department (ED).³⁰ Borro et al found that use of Ag-RDTs to supplement the symptom screening and time-consuming PCR testing was of considerable value in identifying and isolating patients entering the ED who were asymptomatic but infected to minimise spread within long waiting times in ED waiting rooms.³¹ The ability of health systems to adequately respond to emerging global infectious disease threats through integration within health services with high patient volumes, staff shortages and other competing demands may be limited without considering the need for additional human resources.

We also found a high CD in TB clinics compared with MNCH or HIV clinics, not surprising given the similarities between COVID-19 and TB symptoms that may have led to patients attending the TB clinic for diagnoses.³² TB clinics may also benefit from their diagnosis and contact tracing methods. They are also key components of SARS-CoV-2 infection control strategies. In our study, the integration of SARS-CoV-2 services in MNCH, HIV and TB services increased access to SARS-CoV-2 screening and diagnostic testing for these populations at risk for more severe COVID-19 disease.

The SARS-CoV-2 response can learn from the HIV global response where the switch from a risk-screening ‘opt-in’ rapid HIV testing approach to a TA ‘opt-out’ approach to HIV testing in antenatal clinics advanced early progress in the prevention of mother-to-child HIV transmission (PMTCT). Subsequent integration of HIV services, including HIV testing and counselling in non-HIV services using a TA model, improved overall health and health system outcomes including linkage to care with progress towards achievement of the UNAIDS 95-95-95 targets.^{31 33 34} In one example of HIV testing integration in MNCH clinics in Nigeria, only about 10% of pregnant women were receiving PMTCT services prior to integration, and after integration, about 89% were newly enrolled into care.³⁵ Similarly, the integration of point-of-care Ag-RDTs in MNCH, HIV and TB health services has the potential to promptly identify more SARS-CoV-2 infections, promote prompt linkage to care, quarantine and contact tracing, and identify clusters of cases and locations where ongoing or new community infections might have been occurring to prevent spread and improve patient outcomes.

We acknowledge that we were not able to implement the contact tracing component of the study as outlined in the protocol, and as a result, we are unable to present the outcome on contact tracing. We also noted some limitations in our study. Our study was conducted at a time late in the pandemic when the overall SARS-CoV-2 prevalence in both countries was low, which likely affected both healthcare workers’ willingness to provide the screening and/or testing services and the attendees’ willingness to be tested. Reasons for the low SARS-CoV-2 testing ratio in both models of integration in Cameroon and Kenya were not documented, so the relative contribution of reasons such as SARS-CoV-2 testing refusals from clinic attendees, staff reluctance or workload, or a sense of no added value for testing due to decreased COVID-19 waves in both countries was unclear. In addition, the study was implemented in a few sites in selected regions in Kenya and Cameroon; and we also acknowledge that the concentration of facilities in one county may not fully represent the overall epidemiology of disease in Kenya; respiratory viruses transmission dynamics, when localised could indeed affect the study results; thus, the study results may not be generalisable across both countries and globally. Another notable limitation of this study is the potential for including repeat participants in the SARS-CoV-2 CDs calculations. Although repeat testing was offered to those who returned for routine care more than once, provided their previous test was conducted over 2 weeks prior, the possibility of counting the same individual multiple times remains in the study.

Despite the challenges in reaching all clinic attendees with testing, these results can be applicable in other contexts and populations. Our study findings have significant implications for African countries which often face a high burden of infectious disease outbreaks, like Ebola and mpox. Even though the study was conducted in the tail end of the epidemic, we believe that this intervention would be more effective during the epidemic peak. Integration of services such as SARS-CoV-2 Ag-RDT screening and testing or other infectious diseases outbreaks, in the health services can potentially improve access to testing and early identification of more infections; thus, preventing transmission and improving the clinical management and outcomes, particularly important when competing health demands such as HIV and TB among other comorbidities and co-infections are more prevalent. The TA model could be considered in future pandemics, considering the lessons learnt from this study and others. Effective implementation would require additional specific considerations, including identifying when and where integrating SARS-CoV-2 services would be most effective, providing appropriate staffing in the targeted clinics to TA, community sensitisation and demand creation to promote testing uptake and procurement of sufficient commodities to manage the testing volumes. Having accurate and timely test results is critical to limit the time that an infected person spends in the facility and strict adherence to infection control and quarantine procedures.

Data availability statement

Data are available upon reasonable request.