Abstract
Objective:
Data on the impact of coronavirus disease 2019 (COVID-19) in people with HIV (PWH) are lacking in resource-constrained settings. We utilized existing randomized clinical trials (RCTs) on antiretroviral therapies (ART) in HIV-1 infection to conduct a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey, between January and March 2021, while characterizing participants’ features.
Design:
Cross-sectional serosurvey.
Methods:
Demographic characteristics, medical history and a serum sample were collected from consenting PWH. Samples were analyzed centrally for immunoglobulin G antibodies to recombinant nucleocapsid and spike proteins derived from SARS-CoV-2 using a Luminex based assay.
Results:
The 549 participants recruited in 9 sites across Africa had a median age of 40 years (interquartile range, IQR [34–45]); 63.0% (346) were female. All were on ART; 81.8% (449) had an HIV-1 viral load <50 copies/ml, with CD4+ cell count median at 478/mm3 (IQR [320–677]). None had received vaccination against SARS-CoV-2. Forty participants (7.3%) had a prior SARS-CoV-2 PCR testing, of whom 10 were positive (1.8%). Crude SARS-CoV-2 seroprevalence was 36.2% (95% confidence interval (CI) [32.2–40.4]). In the explorative multivariable analysis, comparison of the characteristics of PWH with a positive SARS-CoV-2 serology with those with a negative or indeterminate serology: PWH with a body mass index (BMI) ≥30 kg/m2 were more likely to have a positive serology than those with a BMI <25 (adjusted odds ratio (aOR) = 2.39 [1.48–3.86], P < 0.001); and PWH living in Cameroon were less likely to have a positive serology.
Conclusion:
This study demonstrates a substantial seroprevalence level of SARS-CoV-2 in PWH in the first quarter of 2021, with a marked disparity with the number of COVID-19 PCR tests reported positive.
Keywords: coronavirus disease 2019, people with HIV, randomized clinical trials, serology
Introduction
When the World Health Organization (WHO) declared the coronavirus disease 2019 (COVID-19) pandemic in March 2020, questions arose as whether conditions that impair the immune system were risk factors for severe outcomes for COVID-19 [1]. In addition, in people with HIV (PWH), suspected factors for severe outcomes for COVID-19 (like cardio-vascular [2–4], respiratory [5] or metabolic [6] comorbidities) are known to be more frequent than in the general population [7]. Cohort studies were published across different regions and the WHO launched a first global report [8], underlying HIV-infection was a risk factor for severe outcomes and higher mortality in hospitals. Studies were often focused on hospitalized participants in high-income countries.
We leveraged four ongoing randomized controlled trials (RCTs) on first- and second-line antiretroviral therapy (ART) in low- and middle-income countries to establish a cross-sectional severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey. These RCTs began before the COVID-19 pandemic, and were following-up, or still recruiting participants, in Africa, Asia and Latin America in 2020–2021. The existence of these networks facilitated the organization of this serosurvey planned for the end of first year of COVID-19 pandemic.
The main objective of this study was to evaluate the seroprevalence of SARS-CoV-2, using immunoglobulins (Ig) G, within the international multicentre consortium cohort. The secondary objectives were to describe the cohort and assess if any potential factors were associated with a COVID-19 seropositive result.
Material and methods
Population, study setting and design
COHIVE was a prospective cross-sectional serosurvey nested in ADVANCE [9], D2EFT [10], and NAMSAL [11] cohorts (details in Supplemental material 1). Participants in these RCTs could opt-in to the COHIVE serosurvey when attending their RCT study visit. All participants were invited irrespective of their COVID-19 history. This was a convenience sample with an open-ended sample size. The recruitment period for COHIVE serosurvey was from 1 January 2020 to 31 March 2021.
Severe acute respiratory syndrome coronavirus 2 testing
The serum samples were shipped at constant temperature (storage at −80°Celsius after being aliquoted) and stored at TransVIHMI, IRD, France, where the testing was centrally performed. All serum samples were screened for Ig G antibodies to recombinant nucleocapsid (NC) and spike (S) proteins derived from SARS-CoV-2 using an in-house Luminex based multiplex immunoassay [12]. To ensure a stringent case definition a seropositive result requires both IgG NC and S levels above cut-off values (500 and 1000 MFI/50 beads, respectively), a negative result needed both IgG NC and S levels to be below the cut-off, and all other outcomes were classified as indeterminate. The performance characteristics of this Luminex based assay were defined in diverse settings including Africa, overall accuracy is 100% (S) and 99.9% (NC) [12,13].
Outcomes and data collected
The data collected for COHIVE study included demographic characteristics, smoking history and vaccination status [for seasonal flu, Bacille Calmette-Guerin (BCG), pneumococcus and SARS-CoV-2], any potential exposure, suspicion or confirmation of COVID-19 during the period of interest (from March 2020 to the date of the serosurvey visit in the first quarter of 2021), physical measures (weight and height), medical history and new events characteristics (specifications in Supplemental material 1). HIV-infection parameters retrieved were: time since HIV-1-infection diagnosis, CD4+ nadir, cumulated time on ART, antiretroviral regimen, adherence to ART, and CD4+ level and HIV viral load (VL).
The results for the African countries are presented here, more details on the COHIVE cohorts can be found in Supplemental Material 2.
Statistical analysis
We used descriptive statistics to describe baseline characteristics of the COHIVE participants. Continuous data were reported as median with interquartile range (IQR), and categorial data as proportion and percentage. The crude prevalence was defined as the number of participants with a positive SARS-CoV-2 serology result divided by the total number of participants tested in COHIVE, and presented as a percentage with 95% confidence interval (95% CI). Fisher's exact tests were used to compare categories, and Wilcoxon rank-sum tests were used to compare nonnormal distributed continuous variable (IgG levels).
We assessed factors associated with a positive SARS-CoV-2 IgG result using a multivariable logistic regression analysis. Covariate assessed were: age, sex, country, body mass index (BMI, in kg/m2: ‘healthy’ ≥ 18.5–<25, ‘underweight’ <18.5, ‘overweight’ ≥ 25–<30 and ‘obesity’ ≥ 30 [14]), comorbidities, smoking history, last CD4+ level and HIV VL, CD4+ nadir, time since HIV diagnostic and ART. Variables with a P <0.2 in the univariate analysis were included in the initial multivariable model, before conducting backward-stepwise selection using likelihood ratio to test the model fit. Covariates with P < 0.05 in the multivariable analysis were considered statistically significant. There were no missing data in the variables included in the model.
All analyses were performed using Stata version 18.0 (StataCorp LP, College Station, Texas, USA).
Ethics approval
COHIVE is registered under NCT04371835 and received approval from the UNSW Human Research Ethics Committee (IRB00009153) under number HC200279 dated 24 April 2020, and subsequently from all local Ethics committees. Participants’ written consent was obtained.
Results
Crude seroprevalence
Five hundred and forty-nine participants were enrolled during the first quarter of 2021 in nine research sites across Cameroon, Nigeria, South Africa, and Zimbabwe. The overall crude seroprevalence for SARS-CoV-2 in this sample was of 199/549 (36.2%; 95% CI [32.2; 40.4]). The proportion of participants SARS-CoV-2 seropositive by country was: 42/100 in Nigeria (42.0%; 95% CI [32.2; 52.3]), 110/285 in South Africa (38.6%; 95% CI [32.9; 44.5]), 20/58 in Zimbabwe (34.5%; 95% CI [22.5; 48.1]), and 27/106 in Cameroon (25.5%; 95% CI [17.5; 34.9]).
The distribution of antibodies response was similar in female (IgG anti-NC median: 290.8 [73; 1540.5] and IgG anti-S: 1141.8 [406.5; 2583.0]) and male (IgG anti-NC median: 306.0 [79.0; 1422.0] and IgG anti-S: 1161.0 [413.5; 2720.5]).
Baseline characteristics
Overall, the median age was 40 years old (IQR [34; 45]), 346/549 (60.9%) were female, and participants were diagnosed for HIV-1 infection with a median time of 3.8 years (IQR [3.3; 7.1]). As the sample was drawn from three therapeutic RCTs, all participants were on ART (first or second line, standard of care or experimental regimens), the median of CD4+ cells was 478/mm3 [320; 677], and 449/549 (81.8%) had an HIV VL below 50 copies/ml. Table 1 details the baseline characteristics of the participants.
Table 1.
Participants characteristics (N = 549) at baseline and during the period of interest (March 2020–date of the cross-sectional serosurvey visit in the first quarter of 2021).
| Characteristics | Total | SARS-2 serology positive | SARS-2 serology indeterminate | SARS-2 serology negative |
| n (%)a | n (%)a | n (%)a | n (%)a | |
| Sample size | 549 (100.0) | 199 (36.2) | 123 (22.4) | 227 (41.4) |
| Age – year | ||||
| Median [IQR] | 40 [34–45] | 40 [35–45] | 40 [34–45] | 40 [34–46] |
| Sex | ||||
| Female | 346 (63.0) | 125 (62.8) | 78 (63.4) | 143 (63.0) |
| Male | 203 (37.0) | 74 (37.2) | 45 (36.6) | 84 (37.0) |
| BMIb – kg/m2 | ||||
| Median [IQR] | 25.9 [22.3–29.8] | 26.9 [23.0–31.4] | 25.6 [23.1–28.4] | 24.8 [21.7–29.1] |
| Under weight | 21 (3.8) | 3 (1.5) | 7 (5.7) | 11 (4.8) |
| Healthy weight | 222 (40.5) | 69 (34.7) | 48 (39.0) | 105 (46.3) |
| Overweight | 173 (31.5) | 63 (31.6) | 48 (39.0) | 62 (27.3) |
| Obesity | 133 (24.2) | 64 (32.2) | 20 (16.3) | 49 (21.6) |
| Smoking history | ||||
| Never | 484 (88.2) | 181 (90.9) | 104 (84.6) | 199 (87.7) |
| Current or past | 65 (11.8) | 18 (9.1) | 19 (15.4) | 28 (12.3) |
| Medical history | ||||
| None known | 414 (75.4) | 145 (72.9) | 99 (80.5) | 170 (74.9) |
| One comorbidity | 126 (22.9) | 51 (25.6) | 23 (18.7) | 52 (22.9) |
| Two comorbidities | 8 (1.5) | 3 (1.5) | 1 (0.8) | 4 (1.8) |
| Three comorbidities | 1 (0.2) | 0 | 0 | 1 (0.4) |
| High-blood pressurec | 89 (16.2) | 34 (17.1) | 13 (10.6) | 42 (18.5) |
| Country | ||||
| Cameroon | 106 (19.3) | 27 (13.6) | 33 (26.8) | 46 (20.2) |
| Nigeria | 100 (18.2) | 42 (21.1) | 27 (22.0) | 31 (13.7) |
| South Africa | 285 (51.9) | 110 (55.3) | 57 (46.3) | 118 (52.0) |
| Zimbabwe | 58 (10.6) | 20 (10.0) | 6 (4.9) | 32 (14.1) |
| Lastd CD4+ – /mm3 | ||||
| Median [IQR] | 478 [320–677] | 479 [318–697] | 478 [325–674] | 480 [317–666] |
| Lastd HIV VL | ||||
| <50 copies/ml | 449 (81.8) | 168 (84.4) | 97 (78.9) | 184 (81.1) |
| ≥ 50 copies/ml | 100 (18.2) | 31 (15.6) | 26 (21.1) | 43 (18.9) |
| CD4 nadir – /mm3 | ||||
| <50 | 54 (9.8) | 17 (8.6) | 12 (9.8) | 25 (11.0) |
| 50–99 | 45 (8.2) | 14 (7.0) | 10 (8.1) | 21 (9.3) |
| 100–199 | 114 (20.8) | 49 (24.6) | 19 (15.4) | 46 (20.3) |
| 200–349 | 173 (31.5) | 52 (26.1) | 44 (35.8) | 77 (33.9) |
| 350–499 | 93 (16.9) | 37 (18.6) | 23 (18.7) | 33 (14.5) |
| ≥500 | 70 (12.8) | 30 (15.1) | 15 (12.2) | 25 (11.0) |
| Time HIV – year | ||||
| Median [IQR] | 3.8 [3.3–7.1] | 3.8 [3.3–8.1] | 3.9 [3.3–7.6] | 3.8 [3.3–6.0] |
| Time ART – year | ||||
| Median [IQR] | 3.7 [3.3–4.2] | 3.6 [3.1–4.3] | 3.7 [3.3–4.1] | 3.7 [3.3–4.2] |
| Time undetectablee– years | ||||
| Median [IQR] | 2.3 [0.7; 3.2] | 2.2 [0.8; 3.1] | 2.0 [0.4; 3.1] | 2.5 [0.4; 3.2] |
| ART 3rd agent | ||||
| DTG + DRV/re | 57 (10.4) | 25 (12.6) | 12 (9.8) | 20 (8.8) |
| DTG | 279 (50.8) | 97 (48.7) | 64 (52.0) | 118 (52.0) |
| PI/r | 60 (10.9) | 22 (11.1) | 12 (9.8) | 26 (11.5) |
| EFV 400 | 52 (9.5) | 15 (7.5) | 16 (13.0) | 21 (9.2) |
| EFV 600 | 101 (18.4) | 40 (20.1) | 19 (15.4) | 42 (18.5) |
| ART by NRTIs | ||||
| TAF | 84 (15.3) | 31 (15.6) | 17 (13.8) | 36 (15.9) |
| TDF | 354 (64.5) | 121 (60.8) | 87 (70.7) | 146 (64.3) |
| No TDF/TAF | 111 (20.2) | 47 (23.6) | 19 (15.5) | 45 (19.8) |
| ART by PI/r | ||||
| PI/r | 117 (21.3) | 47 (23.6) | 24 (19.5) | 46 (20.3) |
| No PI/r | 432 (78.7) | 152 (76.4) | 99 (80.5) | 181 (79.7) |
| Adherence to ART | ||||
| All pills everyday | 525 (95.6) | 194 (97.5) | 114 (92.7) | 217 (95.6) |
| Not | 24 (4.4) | 5 (2.5) | 9 (7.3) | 10 (4.4) |
| Secondary outcome | ||||
| None reported | 498 (90.7) | 184 (92.5) | 112 (91.1) | 202 (89.0) |
| One reported | 46 (8.4) | 12 (6.0) | 10 (8.1) | 24 (10.6) |
| Two reported | 5 (0.9) | 3 (1.5) | 1 (0.8) | 1 (0.4) |
| Infectionsf | 52 | 17 | 11 | 24 |
ART, antiretroviral therapy; BMI, body mass index; DRV/r, darunavir boosted with ritonavir; DTG, dolutegravir; EFV400/600, efavirenz 400 or 600 mg; HIV VL, HIV viral load (plasma); IQR, interquartile range; NRTI, nucleos(t)ide reverse transcriptase inhibitor; PI/r, protease inhibitor boosted with ritonavir; TAF, tenofovir alafenamide fumarate; TDF, tenofovir disoproxil fumarate.
Unless otherwise stated in the row headings.
Body mass index (BMI) = weight divided by the squared height (in kg/m2), and categorized it as ‘healthy weight’ (≥18.5 and <25), ‘underweight’ (<18.5), ‘overweight’ (≥25 and <30) and ‘obesity’ (≥30).
High-blood pressure was the comorbidity belonging to medical history/chronic diseases the most often reported.
Lastest known CD4+ level or HIV VL before or at baseline (after March 2020). Time since HIV VL is <50 copies/ml without interruption.
Dual therapy.
Infections were the new event during the period of interest (March 2020–baseline visit) the most often reported (52 events in 47 participants).
High blood pressure was the main chronic disease encountered (89/549; 16.2%), followed by previous pulmonary tuberculosis [20 in total (3.6%); and 7 with a positive SARS-CoV-2 serology].
Fifty-six new events during the period of interest occurred in 51/549 (9.3%) participants. The main event was infections (52).
The vaccination status was also queried for BCG, pneumococcus, and seasonal flu vaccinations. The question was answered by 419/549 (72.4%) of the participants, including Five/549 (1.2%) participants reported an influenza vaccine (2 had a SARS-CoV-2 serology negative, 2 intermediate and 1 positive), and 134/549 (24.4%) a BCG vaccine, of which 39/134 (29.1%) had a SARS-CoV-2 serology positive. During the period of study, no participants had received an immunization against COVID-19.
Suspected cases and confirmed cases of COVID-19
Forty of 549 (7.3%) participants reported they had a COVID-19 PCR test between March 2020 and their cross-sectional serosurvey visit (January–March 2021) with a result, 10/549 (1.8%) were positive and 30 were negative. Among the 10 participants tested positive on a nasopharyngeal swab with a COVID-19 PCR test, 7 had a SARS-CoV-2 serology positive, 2 indeterminate and 1 negative. The positive serologies were up to 11 months after the PCR test. Of the 509 who were never tested with a COVID-19 PCR test during the period of interest, 499 (98.0%) were never suspected of COVID-19 – of those, 174 (34.9%) with a SARS-CoV-2 serology positive – and one was a potential contact but remained asymptomatic for 14 days. The latter had a positive SARS-CoV-2 serology.
None of the participants with a positive COVID-19 PCR had received a COVID-19 targeted treatment.
Multivariable analyses
The univariate analysis performed on the variables listed in Table 1. Table 2 shows the final best fitted model. The factor significantly associated to a seropositive result for SARS-CoV-2 is BMI (aOR: 2.39 [1.48; 3.86], P < 0.001) for BMI≥30 kg/m2 compared to under-/healthy-weight. PWH living in Cameroon had also significantly more negative SARS-CoV-2 serologies.
Table 2.
Univariate and multivariable analyses (N = 549).
| Characteristics | Total | SARS-2 serology positive | Univariate analysisa | Multivariate analysisb |
| n (%) | n (%) | OR, P | aOR [95% CI], P | |
| Sample size | 549 (100.0) | 199 (36.2) | ||
| Age – year | P = 0.785 | |||
| Median [IQR] | 40 [34–45] | 40 [35–45] | 1.0 [0.98; 1.02] | |
| Sex | P = 0.939 | |||
| Male | 203 (37.0) | 74 (37.2) | Ref | Ref |
| Female | 346 (63.0) | 125 (62.8) | 0.98 [0.68; 1.41] | 0.66 [0.43–1.00], P = 0.052 |
| Country | P = 0.050 | |||
| Cameroon | 106 (19.3) | 27 (13.6) | 0.54 [0.33; 0.89] | 0.56 [0.34; 0.92], P = 0.025 |
| Nigeria | 100 (18.2) | 42 (21.1) | 1.15 [0.72; 1.83] | 1.05 [0.62; 1.77], P = 0.866 |
| South Africa | 285 (49.5) | 110 (55.3) | Ref | Ref |
| Zimbabwe | 58 (10.6) | 20 (10.0) | 0.84 [0.46; 1.51] | 0.85 [0.44; 1.63], P = 0.623 |
| BMI – kg/m2 | P = 0.002 | |||
| Under/healthy weight | 243 (44.3) | 72 (36.2) | Ref | Ref |
| Overweight | 173 (31.5) | 63 (31.6) | 1.36 [0.90; 2.06] | 1.47 [0.96–2.27], P = 0.079 |
| Obesity | 133 (24.2) | 64 (32.2) | 2.20 [1.42; 3.41] | 2.39 [1.48–3.86], P < 0.001 |
| Comorbidities | P = 0.299 | |||
| None known | 414 (75.4) | 145 (72.9) | Ref | |
| Yes | 135 (24.6) | 54 (27.1) | 1.23 [0.83; 1.84] | |
| Smoking history | P = 0.120 | |||
| Never | 484 (88.2) | 181 (90.9) | Ref | Ref |
| Current or past | 65 (11.8) | 18 (9.1) | 0.64 [0.36; 1.14] | 0.62 [0.33–1.16], P = 0.135 |
| Last CD4+ – /mm3 | P = 0.960 | |||
| Median [IQR] | 478 [320–677] | 479 [318–697] | 1.00 [0.99; 1.00] | |
| Last HIV VL | P = 0.223 | |||
| <50 copies/ml | 449 (81.8) | 168 (84.4) | Ref | |
| ≥ 50 copies/ml | 100 (18.2) | 31 (15.6) | 1.33 [0.84; 2.12] | |
| CD4 nadir – /mm3 | P = 0.157 | |||
| <50 | 54 (9.8) | 17 (8.6) | Ref | |
| 50–99 | 45 (8.2) | 14 (7.0) | 0.98 [0.42; 2.31] | |
| 100–199 | 114 (20.8) | 49 (24.6) | 1.64 [0.82; 3.25] | |
| 200–349 | 173 (31.5) | 52 (26.1) | 0.94 [0.48; 1.81] | |
| 350–499 | 93 (16.9) | 37 (18.6) | 1.44 [0.71; 2.92] | |
| ≥500 | 70 (12.8) | 30 (15.1) | 1.63 [0.78; 3.44] | |
| Time HIV – year | P = 0.110 | |||
| Median [IQR] | 3.8 [3.3–7.1] | 3.8 [3.3–8.1] | 1.03 [0.99; 1.08] | 1.03 [0.98–1.08], P = 0.214 |
| ART by NRTIs | P = 0.299 | |||
| TAF | 84 (15.3) | 31 (15.6) | 0.80 [0.45; 1.22] | |
| TDF | 354 (64.5) | 125 (60.8) | 0.71 [0.46; 1.09] | |
| No TDF/TAF | 111 (20.2) | 47 (23.6) | Ref |
(a)OR, (adjusted) odd ratio; ART, antiretroviral therapy; BMI, body mass index; HIV VL, HIV viral load (plasma); IQR, interquartile range; 95% CI, 95% confidence interval.
Univariate logistic regression.
Multivariable logistic regression analysis, starting from best subset then backward-stepwise selection using postestimates. P = 0.0013.
Discussion
This sample highlights an important, unexpectedly high seroprevalence level of SARS-CoV-2 in PWH in Africa, in the first quarter of 2021, using a stringent seropositivity definition.
The timing of the COHIVE serosurvey enabled sampling at a time point where participants could have been exposed to the original SARS-CoV-2 and first variants within a year. During the first quarter of 2021, most countries were after the first wave of COVID-19 or entering their second wave (Supplemental material 2) [15]. The number of participants estimated as exposed to SARS-CoV-2 in this study looked consistent with the literature in the African region [13,16–19]. Another serosurvey in Cameroon [20] showed a steep increase in the aged-standardized SARS-CoV-2 IgG prevalence from 18.6% in the first two months of 2021 to 51.3% in April/May 2021. The low number of COVID-19 RT-PCR tests in our sample, which were less readily available in our cohort's setting, was mirrored in South Africa by Wolter et al.[21].
This cohort of PWH on suppressive ART and with a facilitated access to healthcare (and sustainable ART procurement) thanks to their participation in an RCT pinpointed that PWH could present with asymptomatic COVID-19, or at least no severe symptoms. This was already demonstrated in the RETRIEVE cohort [22], and also aligned with the findings from the cohort of the Spanish HIV Research Network [23]. However, as opposed to the latter and an American study [24], we did not find a protective effect from TDF.
Participants presenting an obesity (based on the baseline BMI) had more chance to be seropositive for SARS-CoV-2. Even if potential confoundings could not be thoroughly explored in COHIVE study, this finding aligns with observations in various settings [25,26].
These observations differed from the World Health Organization report [8] highlighting more severe outcomes and a higher mortality in PWH when hospitalized compared to the general population. Beyond the optimal follow-up of PWH in RCTs, we may have missed PWH with severe symptoms of COVID-19 who did not attend their RCT visit during the COHIVE enrolment window.
The main limitations of our study are linked to the multicentre cross-sectional design, and convenience sample of RCTs’ participants making it unrepresentative of the overall PWH community. Inferences on factors associated to the exposure to COVID-19, must be treated with caution. We have missed some confounding factors as our survey did not include individual socio-economic data, and more data are needed around the dynamic of IgG anti-S and NC, after exposure to COVID-19.
Conclusion
This SARS-CoV-2 cross-sectional serosurvey implemented in the first quarter of 2021 showed a high seroprevalence compared to the low number of suspected COVID-19 infection in this population. Acknowledging this type of study is exploratory, the signal around BMI, with higher BMI related to a positive result, could guide research questions for larger studies to ascertain characteristics in PWH which are associated with COVID-19 severe outcomes or protection against COVID-19, which are needed to guide allocation of prevention tools for COVID-19 like vaccination or screening, particularly in resource-constrained countries.
Acknowledgements
The authors gratefully acknowledge the contribution of all participants and of the ADVANCE, DolPHIN2, D2EFT and NAMSAL Study Groups (present representatives listed below, and deceased: Prof. David Cooper, Prof. James Gita Hakim, Dr Ernest Ekong and Ms. Celicia M. Serenata), the support of the D2EFT community representatives (chair: Leonardo Perelis), the assistance of the IT group (Mr. Yuvi Ghodke & Mr. Noorul Absar) and the participation of the patients, healthcare givers, and researchers in ADVANCE, DolPHIN2, D2EFT and NAMSAL projects.
The authors also gratefully acknowledge the support of the other academic collaborators (Dr H. Clifford Lane; NIH), institutional collaborators (WHO and CHAI) and funding partners (Unitaid, ANRS|MIE, NIH, NHMRC and ViiV Healthcare).
Author contributions: E.P. and M.N.P. conceived and designed the study. A.C., E.D., F.V., J.W., K.P., M.A., S.K. and T.T.S. critically reviewed and participated in the development of the protocol. All authors critically reviewed the protocol. A.A., B.G., C.K., I.A., J.W., M.B., M.M.E., N.E., N.K., R.K. and S.S. participated in data acquisition. A.A. and G.T. conducted the serological analyses. E.P. and K.P. analysed and interpreted the data. E.P. drafted the article. All authors revised the article critically for important intellectual content. All authors have given final approval for publication and take responsibility for the integrity of the data. M.N.P. had full access to all data in the study and had final responsibility for decision to submit the article for publication.
COHIVE Consortium (alphabetical order for each sub-groups)
Coordinating principal investigators: Prof Alexandra Calmy (President of NAMSAL Scientific Board), Prof Eric Delaporte (NAMSAL Coordinating Principal Investigator – North CMG), Prof Saye Khoo (DolPHIN2 Coordinating Principal Investigator), Dr Charles Kouanfack (NAMSAL Coordinating Principal Investigator – South CMG), Dr Emmanuelle Papot (Protocol lead investigator for COHIVE; D2EFT), A/Prof Mark Polizzotto (coordinating chair for COHIVE; D2EFT Coordinating Principal Investigator), Prof W. D. Francois Venter (ADVANCE Coordinating Principal Investigator), Dr Joana Woods (ADVANCE).
Co-investigators: Dr Anchalee Avihingsanon (D2EFT Principal Investigator, Thailand), Dr Iskandar Azwa (D2EFT Principal Investigator, Malaysia), Dr Nnakelu Eriobu (D2EFT Principal Investigator, Nigeria), Prof James Gita Hakim (D2EFT Principal Investigator, Zimbabwe – March 2020-February 2021) and Prof Margaret Borok (D2EFT Principal Investigator, Zimbabwe – from February 2021), Dr Richard Kaplan (D2EFT Principal Investigator, South Africa), Dr Nagalingesawaran Kumarasamy (D2EFT Principal Investigator, India), Dr Mohammed Lamorde (DolPHIN2 Principal Investigator, Uganda), Prof Matthew Law (statistical conduct, D2EFT), Dr Mireille Mpoudi-Etame (NAMSAL Principal Investigator, Military Hospital Cameroon), Dr Marcelo H. Losso (D2EFT Principal Investigator, Latin America), Prof Landon Myer (DolPHIN2 Principal Investigator, South Africa), A/Prof Kathy Petoumenos (statistical conduct COHIVE), Dr Catriona Waitt (DolPHIN2); Protocol team: Dr Maria Arriaga (coordinator for COHIVE), Ms Michelle Burns (D2EFT), Ms Simone Jacoby (D2EFT), Ms Claire Murzeau (NAMSAL), Ms Helen Reynolds (DolPHIN2), Ms Celicia M. Serenata (ADVANCE), Dr Tamara Tovar Sanchez (NAMSAL).
ADVANCE study group (alphabetical order for each sub-groups)
Ezintsha (Wits Health Consortium): Esther Bhaskar, Bronwyn Bosch, Ncomeka Manentsa, Nkuli Mashabane, Nkoleleng Mashilo, Karlien Moller, Simiso Sokhela, Ineeleng Taukobong, Noxolo Tom, Francois Venter, Joana Woods.
DolPHIN2 study group (alphabetical order for each sub-groups)
University of Liverpool, UK: Ms. Helen Reynolds, Prof. Saye Khoo, Dr Catriona Waitt. Infectious Diseases Institute, Kampala, Uganda: Dr Mohammed Lamorde. School of Public Health and Family Medicine, University of Cape Town, South Africa: Prof. Landon Myer.
D2EFT Study group (alphabetical order for each sub-groups)
The Kirby Institute: Eamon Brown, Michelle Burns, Ai Caldis, Cate Carey, Megan Clewett, David Cooper, Sean Emery, Yuvaraj Ghodke, Simone Jacoby, Anthony Kelleher, Matthew Law, Margaret Lowe, Gail V. Matthews, Emmanuelle Papot, Mark N. Polizzotto, David Silk.
Protocol Steering Committee: Iskandar Azwa, Margaret Borok, Dannae Brown, Mohamed Cisse, Sounkalo Dao, Nnakelu Eriobu, Simone Jacoby, Richard Kaplan, Muhammad Karyana, Anthony Kelleher, Nagalingeswaran Kumarasamy, H. Clifford Lane, Matthew Law, Johnnie Lee, Marcelo H. Losso, Gail V. Matthews, Leonardo Perelis, Carmen Perez-Casas, Mark N. Polizzotto, Kiat Ruxrungtham, Jean Van Wyk, Melynda Watkins.
Country teams: Argentina (Patricia Burgoa, Marcelo H. Losso, Sergio Lupo, Luciana Peroni, Renzo Moretto, Ana Melisa Solari, Silvina Tavella, Maria Ines Vieni Deborah Vanina Villegas); Brazil (Kelly Gama, Beatriz Grinsztejn); Chile (Gladys Allendes, Marcelo Wolff); Colombia (Ana Julia Rojas, Otto Sussmann); Guinea (Mohamed Cisse, Mariama Sadjo Diallo, Mohamed Macire Soumah, Thierno Mamadou Tounkara); India (Faith Beulah, Nagalingeswaran Kumarasamy, Poongulali Selvamuthu); Indonesia (Yusrina Adani, Dona Arlinda, Yufi Aulia Azmi, Usman Hadi, Sudirman Katu, Munawir Muhammad, Nur Herda Wati Nisa, Yanri Wijayanti Subronto, Evy Yunihastuti); Malaysia (Iskandar Azwa, Farhana Nadiah Abd Ghani, Chow Ting Soo, Margaret Tan); Mali (Sounkalo Dao, Yacouba Cissoko); Mexico (Jaime Andrade-Villanueva, Juan Luis Mosqueda G omez, Fernando Amador Lara, Juan Sierra Madero, Sergio del Moral Ponce, Jorge Morales Varges); Nigeria (Maryam Al-Mujtaba, Peter Ekele, Nnakelu Eriobu, Lanre Falodun); Thailand (Anchalee Avihingsanon, Ploenchan Chetchotisakd, Sivaporn Gatechompol, Suwimon Khusuwan, Weerawat Manosuthi, Supawadee Pongprapass, Kanitta Pussadee, Supeda Thongyen, Anchalee Tiyabut); South Africa (Desiree Van Amsterdam, Jaclyn Ann Bennet, Richard Kaplan, Lerato Mohapi, Suri Moonsamy, Mary Sihlangu); Zimbabwe (Margaret Borok, Ennie Chidziva).
NAMSAL study group
TransVIHMI, University of Montpellier – IRD-UMI233 – INSERM-U1175, Montpellier, France: E Delaporte, A Ayouba, A Agholeng, C Butel, B Granouillac, A Lacroix, S Leroy, M Peeters, R Pelloquin, L Serrano, J Reynes, T Tovar-Sanchez, N Vidal; Central Hospital of Yaoundé, Yaoundé, Cameroon: C Kounfack, M Foalem, PJ Fouda, R Mougnoutou, J Olinga, V Omgba, SC Tchokonte Ngandé, B Ymele; Military Hospital of Yaoundé, Yaoundé, Cameroon: M Mpoudi-Etamé, L Donfack, A Kambi, CD Epoupa Mpacko, M Fotso, R Moukoko, T Nké; District of the Cité Verte Hospital, Yaoundé, Cameroon: P Omgba Bassega, A Akamba, S Lekelem, S Ngono, SB Tongo Fotack, M Tanga, M Tsafack; Cameroon ANRS site, Yaoundé, Cameroon: A Bissek, L Ciaffi, S. Lem, ED Mimbé, M Niba, Camille N, J Olinga, M Varloteaux; CREMER, Yaoundé, Cameroon: E Mpoudi-Ngolé, E Ebong, N Lamare, G Edoul Mbesse, M Tongo; SESSTIM, University of Aix Marseille – IRD – INSERM-UMR1252, Marseille, France: S Boyer, M Bousmah, P Huynh, G Maradan, ML Nishimwe, B Spire; Pharmacology-Toxicology Unit, INSERM-University of Paris Diderot, Paris, France: G Peytavin, MP Lê; ANRS-Inserm, Paris, France: Y Yazdanpanah, A Diallo, I Fournier, A Montoyo, N Mercier, V Petrov-Sanchez, J Jean-Rassat, C Rekacewicz; UNITAID, Geneva, Switzerland: C Perez Casas.
Funding
This work was supported by Unitaid [grant number 2016-09-UNSW].
Funding for ADVANCE is provided by ViiV Healthcare [study reference number: 207441] and Unitaid [grant number 2016-07-Wits RHI].
Funding for the D2EFT study is provided by Unitaid [grant number: 2016-09-UNSW], National Health and Medical Research Council [grant number: APP1104610], ViiV Healthcare [ViiV Study reference number: 207460]. This project has been funded in part with Federal funds from the National Institute of Allergy and Infectious Disease (NIAID) under contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views and policies of the Department of Health and Human Services, nor does mention of the trade names, commercial products, or organizations imply endorsement by the U.S. Government. This research has been funded in part by the National Institutes of Health (by NCI Contract No. HHSN261201500003I, Task Order No. HHSN26100013). The study drugs in D2EFT (namely darunavir and dolutegravir) were donated by ViiV and Janssen.
Funding for the NAMSAL-ANRS12313 study was provided by ANRS|Emerging Infectious Diseases [grant number: NAMSAL-ANRS-12313] and Unitaid [grant number: 2016-03-IBB].
Funding for DolPHIN2 study was provided by Unitaid, with dolutegravir donated by ViiV Healthcare.
The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of Unitaid or any other agency.
Conflicts of interest
A.A.v., A.A.y., A.C., B.G., C.K., E.D., E.P., G.T., I.A., J.W., K.P., M.A., M.B., M.H.L., M.M.E., N.E., N.K., R.K., S.J., S.S. and T.T.S. declared no conflicts of interest. G.V.M. received research funding (to institution) from ViiV Healthcare and Janssen for D2EFT study. MNP received research funding (to institution) from ViiV Healthcare, Gilead, Janssen and Bristol Myers Squibb. S.K. reports grants from Gilead Sciences, Merck Sharp & Dohme, and Janssen; and grants and personal fees from ViiV Healthcare, outside of the submitted work. W.D.F.V. received honoraria for educational talks and advisory board membership for Gilead, ViiV, Mylan/Viatris, Merck, Adcock-Ingram, Aspen, Abbott, Roche, J&J, Sanofi, Boehringer Ingelheim, Thermo-Fischer and Virology Education; and research funding to institution from the Bill and Melinda Gates Foundation, SA Medical Research Council, NIH, Unitaid, FIND, Merck, CIFF, USAID, and others, and receives drug donations and financial support for studies from, or did investigator-led studies with, multiple pharmaceutical and biotech companies.
Supplementary Material
COHIVE consortium includes ADVANCE, DolPHIN2, D2EFT and NAMSAL study groups, as listed in the Acknowledgements section.
Supplemental digital content is available for this article.
Data availability statement:
The data underlying this article are available in the article.
References
- 1.Geretti AM, Stockdale AJ, Kelly SH, Cevik M, Collins S, Waters L, et al. Outcomes of COVID-19 related hospitalization among people with HIV in the ISARIC WHO Clinical Characterization Protocol (UK): a prospective observational study. Clin Infect Dis 2020; 73:e2095–e2106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Boccara F, Lang S, Meuleman C, Ederhy S, Mary-Krause M, Costagliola D, et al. HIV and coronary heart disease: time for a better understanding. J Am Coll Cardiol 2013; 61:511–523. [DOI] [PubMed] [Google Scholar]
- 3.Kovari H, Calmy A, Doco-Lecompte T, Nkoulou R, Marzel A, Weber R, et al. Antiretroviral drugs associated with subclinical coronary artery disease in the Swiss Human Immunodeficiency Virus Cohort Study. Clin Infect Dis 2020; 70:884–889. [DOI] [PubMed] [Google Scholar]
- 4.Ryom L, Lundgren JD, El-Sadr W, Reiss P, Kirk O, Law M, et al. Cardiovascular disease and use of contemporary protease inhibitors: the D:A:D international prospective multicohort study. Lancet HIV 2018; 5:e291–e300. [DOI] [PubMed] [Google Scholar]
- 5.Fitzpatrick ME, Kunisaki KM, Morris A. Pulmonary disease in HIV-infected adults in the era of antiretroviral therapy. AIDS 2018; 32:277–292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Capeau J, Bouteloup V, Katlama C, Bastard JP, Guiyedi V, Salmon-Ceron D, et al. Ten-year diabetes incidence in 1046 HIV-infected patients started on a combination antiretroviral treatment. AIDS 2012; 26:303–314. [DOI] [PubMed] [Google Scholar]
- 7.Winston A, De Francesco D, Post F, Boffito M, Vera J, Williams I, et al. Comorbidity indices in people with HIV and considerations for COVID-19 outcomes. AIDS 2020; 34:1795–1800. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.WHO. Clinical features and prognostic factors of COVID-19 in people living with HIV hospitalized with suspected or confirmed SARS-CoV-2 infection. In: WHO Global Clinical Platform for COVID-19 – data for public health response. Geneva: World Health Organization; 2021. [Google Scholar]
- 9.Venter WDF, Sokhela S, Simmons B, Moorhouse M, Fairlie L, Mashabane N, et al. Dolutegravir with emtricitabine and tenofovir alafenamide or tenofovir disoproxil fumarate versus efavirenz, emtricitabine, and tenofovir disoproxil fumarate for initial treatment of HIV-1 infection (ADVANCE): week 96 results from a randomised, phase 3, noninferiority trial. Lancet HIV 2020; 7:e666–e676. [DOI] [PubMed] [Google Scholar]
- 10.Papot E, Jacoby S, Arlinda D, Avihingsanon A, Azwa I, Borok M, et al. Adaption of an ongoing clinical trial to quickly respond to gaps in changing international recommendations: the experience of D(2)EFT. HIV Res Clin Pract 2022; 23:37–46. [PMC free article] [PubMed] [Google Scholar]
- 11.NAMSAL ANRS 12313 Study Group, Kouanfack C, Mpoudi-Etame M, Omgba Bassega P, Eymard-Duvernay S, Leroy S, et al. Dolutegravir-based or low-dose efavirenz-based regimen for the treatment of HIV-1. N Engl J Med 2019; 381:816–826. [DOI] [PubMed] [Google Scholar]
- 12.Ayouba A, Thaurignac G, Morquin D, Tuaillon E, Raulino R, Nkuba A, et al. Multiplex detection and dynamics of IgG antibodies to SARS-CoV2 and the highly pathogenic human coronaviruses SARS-CoV and MERS-CoV. J Clin Virol 2020; 129:104521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Nkuba AN, Makiala SM, Guichet E, Tshiminyi PM, Bazitama YM, Yambayamba MK, et al. High prevalence of anti-SARS-CoV-2 antibodies after the first wave of COVID-19 in Kinshasa, Democratic Republic of the Congo: results of a cross-sectional household-based survey. Clin Infect Dis 2021; 74:882–890. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.World Health Organization. Global health observatory – nutrition: BMI. https://www.who.int/data/gho/data/themes/topics/topic-details/GHO/body-mass-index. [Google Scholar]
- 15.Worldometer. Coronavirus statistics. https://www.worldometers.info/coronavirus/; 2023. [Google Scholar]
- 16.Soumah AA, Diallo MSK, Guichet E, Maman D, Thaurignac G, Keita AK, et al. High and rapid increase in seroprevalence for SARS-CoV-2 in Conakry, Guinea: results from 3 successive cross-sectional surveys (ANRS COV16-ARIACOV). Open Forum Infect Dis 2022; 9:ofac152. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Sagara I, Woodford J, Kone M, Assadou MH, Katile A, Attaher O, et al. Rapidly increasing SARS-CoV-2 seroprevalence and limited clinical disease in three Malian communities: a prospective cohort study. Clin Infect Dis 2022; 74:1030–1038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Mulenga LB, Hines JZ, Fwoloshi S, Chirwa L, Siwingwa M, Yingst S, et al. Prevalence of SARS-CoV-2 in six districts in Zambia in July, 2020: a cross-sectional cluster sample survey. Lancet Global Health 2021; 9:e773–e781. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Diallo MSK, Amougou-Atsama M, Ayouba A, Kpamou C, Mimbe Taze ED, Thaurignac G, et al. Large diffusion of severe acute respiratory syndrome coronavirus 2 after the successive epidemiological waves, including Omicron, in Guinea and Cameroon: implications for vaccine strategies. Open Forum Infect Dis 2023; 10:ofad216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ndongo FA, Guichet E, Mimbé ED, Ndié J, Pelloquin R, Varloteaux M, et al. Rapid increase of community SARS-CoV-2 seroprevalence during second wave of COVID-19, Yaoundé, Cameroon. Emerg Infect Dis 2022; 28:1233–1236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Wolter N, Tempia S, von Gottberg A, Bhiman JN, Walaza S, Kleynhans J, et al. Seroprevalence of severe acute respiratory syndrome coronavirus 2 after the second wave in South Africa in human immunodeficiency virus-infected and uninfected persons: a cross-sectional household survey. Clin Infect Dis 2022; 75:e57–e68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Overton ET, Weir IR, Zanni MV, Fischinger S, MacArthur RD, Aberg JA, et al. Asymptomatic SARS-CoV-2 infection is common among ART-treated people with HIV. J Acquir Immune Defic Syndr 2022; 90:377–381. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Berenguer J, Díez C, Martín-Vicente M, Micán R, Pérez-Elías MJ, García-Fraile LJ, et al. Prevalence and factors associated with SARS-CoV-2 seropositivity in the Spanish HIV Research Network Cohort. Clin Microbiol Infect 2021; 27:1678–1684. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lea AN, Leyden WA, Sofrygin O, Marafino BJ, Skarbinski J, Napravnik S, et al. Human immunodeficiency virus status, tenofovir exposure, and the risk of poor coronavirus disease 19 outcomes: real-world analysis from 6 United States cohorts before vaccine rollout. Clin Infect Dis 2023; 76:1727–1734. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Beaumont A, Durand C, Ledrans M, Schwoebel V, Noel H, Le Strat Y, et al. Seroprevalence of anti-SARS-CoV-2 antibodies after the first wave of the COVID-19 pandemic in a vulnerable population in France: a cross-sectional study. BMJ Open 2021; 11:e053201. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Montes-Herrera D, Muñoz-Medina JE, Fernandes-Matano L, Salas-Lais AG, Hernández-Cueto M, Santacruz-Tinoco CE, et al. Association of obesity with SARS-CoV-2 and its relationship with the humoral response prior to vaccination in the state of Mexico: a cross-sectional study. Diagnostics 2023; 13:2630. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data underlying this article are available in the article.