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PLOS ONE logoLink to PLOS ONE
. 2024 Aug 7;19(8):e0308568. doi: 10.1371/journal.pone.0308568

Factors associated with SARS-CoV-2 infection among people living with HIV: Data from the Balearic cohort (EVHIA)

Francisca Artigues Serra 1,*, Sophia Pinecki Socias 1, Francisco Javier Fanjul 1, Maria Peñaranda 1, Francisco Homar 2, Patricia Sorni 2, Julia Serra 3, Adelaida Rey 3, Lola Ventayol 4, Maria Dolores Macia 5, Maria Àngels Ribas 1, Melchor Riera 6
Editor: Jake M Pry7
PMCID: PMC11305541  PMID: 39110761

Abstract

Introduction

The impact of SARS-CoV-2 infection among people living with HIV (PLWH) has been a matter of research. We evaluated the incidence and factors associated with SARS-CoV-2 diagnosis among PLWH. We also assessed factors related to vaccination coverage in the Balearic Islands.

Methods

A retrospective analytical study was performed, including patients from the Balearic cohort (EVHIA) who were visited at least twice between 1st January 2020 and 31st March 2022. Chi-square test and Mann-Whitney U test were used to compare categorical and continuous variables respectively. Multivariable Cox proportional hazards regression models were estimated to identify risk factors.

Results

A total of 3567 patients with HIV were included. The median age was 51 years (IQR 44–59). Most of them were male (77,3%), from Europe (82,1%) or South America (13,8%). During the study period 1036 patients were diagnosed with SARS-CoV-2 infection (29%). The incidence rate was 153,24 cases per 1000 person-year. After multivariable analysis, men who have sex with men (MSM) were associated with an increased risk of SARS-CoV-2 infection (adjusted hazard ratio 1,324, 95% CI 1,138–1,540), whereas African origin, tobacco use and complete or booster vaccination coverage were negatively related. Overall, complete vaccination or booster coverage was recorded in 2845 (79,75%) patients. When analysing vaccination uptake, older patients (adjusted hazard ratio 5,122, 95% CI 3,170–8,288) and those with a modified comorbidity index of 2–3 points (adjusted hazard ratio 1,492, 95% CI 1,056–2,107) had received more vaccine doses.

Conclusions

In our study no HIV related factor was associated with an increased risk of SARS-CoV-2 infection, except for differences in the transmission route. Possible confounding variables such as mask wearing or social interactions could not be measured. Vaccines were of utmost importance to prevent SARS-CoV-2 infection. Efforts should be made to encourage vaccination in those groups of PLWH with less coverage.

Introduction

The number of cases of SARS-CoV-2 infection increased worldwide, extensively affecting Spain. First laboratory-confirmed case of SARS-CoV-2 infection in Spain was reported on 31st January 2020 [1]. By the end of March 2022, a total of 6 epidemic periods had been described [2]. The Balearic Islands reported 268.000 SARS-CoV-2 confirmed cases and more than 1.300 deaths during these six waves [3].

A growing concern regarding the consequences of this novel infection among people living with HIV (PLWH) led to substantial research. Current evidence suggests that PLWH receiving effective antiretroviral therapy (ART) are not at higher risk of acquiring SARS-CoV-2 infection than general population [4]. However, socioeconomic and racial disparities have been described, with higher infection rates in low income areas and minority groups [5, 6]. Some risk factors associated with hospital admission and critical illness due to SARS-CoV-2, such as male sex and cardiovascular or respiratory diseases [6, 7], are prevalent among PLWH [8, 9]. Immunosuppression and detectable HIV viremia have been suggested as specific risk factors for severe outcomes [10, 11].

Since the beginning of the SARS-CoV-2 pandemic, the possibility that some antiretroviral drugs may have activity against SARS-CoV-2 infection has been studied, mainly including protease inhibitors and nucleotide/nucleoside reverse-transcriptase inhibitors [12, 13]. However, considering current evidence, no consistent recommendation about changing antiretroviral treatment can be made.

On the other hand, vaccines are a fundamental tool to reduce infection severity and mortality rates. COVID-19 vaccination in Spain started on 27th December 2020, including either 1 dose of Janssen (AD26.COV2.S) or 2 doses of Pfizer-BioNTech (BNT162b2), Moderna (mRNA-1273) or AstraZeneca (ChAdOx1). In a first stage, inmates, health and social health workers in elderly and disabled nursing homes were prioritized, as well as front-line healthcare workers and people with disabilities [14]. Vaccination was progressively opened according to age groups. A booster dose was introduced in October 2021, and an additional dose was advised for people belonging to very high-risk groups [15]. Overall, vaccination coverage in Spain has been high, with 92.9% of the population over 12 years fully vaccinated by 3rd January 2023 [16].

Despite increasing data on HIV and SARS-CoV-2 coinfection, some aspects are still poorly characterized. The aim of our study was to describe the incidence of SARS-CoV-2 in the Balearic HIV cohort (EVIHA) and define risk factors associated with SARS-CoV-2 primoinfection. Additionally, we analyzed epidemiological and clinical factors associated with vaccination uptake in our cohort.

Material and methods

Study population and design

We carried out a retrospective analytical study among PLWH included in the Balearic cohort. Almost all HIV care in the Balearic Islands is provided in public hospitals. The cohort has been monitored since 1998 through the eVIHa clinical platform, with the progressive participation of the four public hospitals in Majorca, and more recently from Minorca and Ibiza as well. It is an open, multicenter, observational cohort which prospectively includes all newly diagnosed patients aged 18 years or older, as well as transferred patients from other autonomous communities or other countries. It monitors sociodemographic data, comorbidities, cardiovascular risk factors, virological data, CD4 cell count, past and present antiretroviral treatments, among other data. Most information is automatically collected from electronic health care system records, laboratory and electronic prescription. All patients signed an informed consent document prior to their inclusion. They receive medical care at least every six months, with routine blood tests. Methodological, ethical and legal aspects of the eVHIa protocol code were approved by the Research Ethics Committee of the Balearic Islands.

Patients who had received telephone or in person medical visit at least twice between 1st January 2020 and 31st March 2022 were eligible for study inclusion. Patients were followed until SARS-CoV-2 infection diagnosis, death, transfer to another autonomous community or country, lost follow-up or until end of the study. This time points were chosen as the moment in which SARS-CoV-2 started to circulate in Europe, until the publication of a modification in the Spanish Healthcare System’s protocol in which only severe cases or vulnerable groups should be tested. Individual notification in Spain was eliminated on 28th March 2022.

Study variables

Information regarding SARS-CoV-2 infection was taken from the sanitary database of the Balearic autonomous community and from hospital reports. In most cases, confirmation of SARS-CoV-2 infection was obtained by means of a PCR test of respiratory samples, mainly nasopharyngeal specimens, and/or antigen detection, which was available in Spain in July 2021.

Sociodemographic variables included age, gender, origin, and tobacco use. Underlying medical conditions were also taken as variables. A modified Charlson index was calculated, considering acquired immunodeficiency syndrome (AIDS) as 1 point instead of 6 points. Among HIV-associated variables, we considered HIV transmission group, CDC category, naive CD4 cell count, tenofovir-based antiretroviral therapy at the beginning of the study, and HIV viral load (VL), CD4 cell count and CD4/CD8 ratio before SARS-CoV-2 infection or at the end of follow-up in those patients who didn’t present coinfection. Undetectable viral load was considered when it was equal or lower than 50 copies per mL.

The type of vaccines before SARS-CoV-2 infection or until the end of follow-up, as well as the administration dates, were collected. The whole vaccination coverage regardless of SARS-CoV-2 infection was also recorded. Vaccination status was considered as unvaccinated or incomplete vaccination when receiving non doses or only 1 dose of Pfizer-Biontech (Cominarty), Moderna or AstraZeneca or others SARS-CoV-2 vaccines accepted in the European Union. Complete vaccination was considered when receiving 2 doses of the previous vaccines or 1 dose of Janssen. Individuals having received 3 or more doses of Pfizer-Biontech, Moderna or AstraZeneca or one dose of Janssen and a second dose of any other vaccine were referred as booster status.

Data was accessed between November 2022 and October 2023 for research purposes. Authors had also access to individual information if required.

Statistical analysis

Categorical variables were expressed as total numbers (percentage), whereas continuous variables were expressed as median (interquartile range, IQR). Baseline characteristics of our cohort were described using proportions (accumulated incidence). Categorical variables were compared with Chi-square test, while Mann-Whitney U test was used in continuous variables. Hazard Ratios (HR) with 95% confidence interval (CI) were calculated to identify risk factors associated with SARS-CoV-2 diagnosis. Multivariable Cox proportional hazards regression models were estimated to identify risk factors, and discriminate cofounders. In the multivariable model, we adjusted for age, country of origin, HIV exposure group, tobacco use, CDC category, modified Charlson Index, plasma HIV viral load, tenofovir-based regimen, CD4 cell count and vaccination regimen.

We used univariate logistic regression to assess the factors associated with vaccination uptake. We calculated Odds ratios (OR) with 95% CI to assess the strength of association to the infection.

Records of missing values for adjustment covariates were excluded in the adjusted analyses, as there were few of them and they were not expected to affect estimates significantly. The level of significance of p was set at <0.05.

Statistical analysis was performed using SPSS 24.0.

Results

Descriptive analysis of our study population

Our study population included 3567 patients who met the inclusion criteria. A total of 3411 patients were still monitored by the end of the study, while 107 patients were lost follow-up and 49 died.

The main characteristics of our study population are shown in Table 1. Shortly, 2758 (77,3%) were male. The median age of the study population was 51 years (IQR 44–59). Overall, 2930 (82,1%) patients originated from Europe, 493 (13,8%) from South America, 117 (3,3%) from Africa and 27 (0,8%) from elsewhere. The main transmission route was through men who have sex with men (MSM) (41,6%), followed by heterosexual relations (31,4%) and injecting drug users (IDU) (20,9%). The median time living with HIV was 14,6 years (IQR 7,5–24,3). Regarding other underlying medical conditions, 1199 (33,6%) patients had a modified Charlson Index higher than 1, including hypertension, dyslipidemia, obesity, chronic HCV infection and chronic obstructive pulmonary disease as the most frequent comorbidities.

Table 1. Descriptive analysis of PLWH included in our study with and without SARS-CoV-2 infection.

Study population (N = 3567) SARS-CoV-2 negative (N = 2531) SARS-CoV-2 positive (N = 1036) p-value
Sex             0,064
Male 2758 77,3% 1978 71,7% 780 28,3%
Female 809 22,7% 553 68,4% 256 31,6%
Age, years             <0,005
median (IQR) 51 (44–59) 52 (45–59) 49 (41–57)
<35 336 9,4% 196 58,3% 140 41,7%
36–50 1260 35,3% 844 67,7% 416 33,0%
51–65 1666 46,7% 1248 74,9% 418 25,1%
66–80 277 7,8% 220 79,4% 57 20,6%
80–95 27 0,8% 22 81,5% 5 18,5%
missing 1 0,0% 1    
Origin             <0,005
Europe 2930 82,1% 2095 71,5% 835 28,5%
Africa 117 3,3% 95 81,2% 22 18,8%
South America 493 13,8% 317 64,3% 176 35,7%
Others 27 0,8% 24 88,9% 3 11,1%
HIV transmission route             <0,001
HTX 1121 31,4% 816 72,8% 305 27,2%
IDU 747 20,9% 562 75,2% 185 24,8%
MSM 1484 41,6% 999 67,3% 485 32,7%
others 50 1,4% 32 64,0% 18 36,0%
unknown 165 4,6% 122 73,9% 43 26,1%
Tobacco use           0,515
Smoker 1190 33,4% 859 72,2% 331 27,8%
Ex-smoker 530 14,9% 374 70,6% 156 29,4%
Non-smoker 1847 51,78 1298 70,3% 549 29,7%
CDC clinical category         0,001
Category A 2259 63,3% 1561 69,1% 698 30,9%
Category B / C 1308 36,7% 970 74,2% 338 25,8%
Years since HIV diagnosis 14,6 (7,5–24,3) 15,3 (8,3–24,9) 13 (6,4–22,4) <0,005
CD4 nadir 274 (131–427) 267 (124–416) 297 (161–466) <0,005
CD4 cell count before infection or end of study period (cells per uL)           0,079
median (IQR) 783 (550–1061) 777 (540–1051) 794 (567–1078)
<200 100 2,82% 71 71,0% 29 29%
200–349 240 6,76% 181 75,4% 59 24,6%
350–500 384 10,82% 290 75.5% 94 24,5%
>500 2825 79,60% 1985 70,3% 840 29,7%
CD4/CD8 before infection or end of study period       0,301
median (IQR) 0,84 (0,56–1,18) 0,84 (0,54–1,18) 0,84 (0,59–1,2)
<0.8 1528 42,8% 1124 73,6% 404 26,4%
0.8–1 571 16,0% 432 75,7% 139 24,3%
>1 1238 34,7% 894 72,2% 344 27,8%
missig 230 6,4% 81 35,21% 149 64,78%
VL>50 before infection or end of study period             0,981
No 3328 93,3% 2371 71,2% 957 28,8%
Yes 222 6,2% 158 71,2% 64 28,8%
missing 17 0,5% 2 11,8% 15 88,2%
VL detectable at any point during the study period             0,45
No 2899 81,3% 2065 71,2% 834 28,8%
Yes 668 18,7% 466 69,8% 202 30,2%
Tenofovir-based regimen             0,608
No 1350 37,8% 963 71,3% 387 28,7%
yes 2168 60,8% 1529 70,5% 639 29,5%
missing 49 1,4% 39 79,6% 10 20,4%
Vaccionation regimen before infection or end of study period       0,001
Unvaccinated or incomplete 1103 30,9% 488 44,2% 615 55,8%
Complete 1002 28,1% 690 68,9% 312 31,1%
Booster 1462 41,0% 1353 92,5% 109 7,5%
Modified Charlson Index             <0,005
0–1 2368 66,4% 1626 68,7% 742 31,3%
2–3 354 9,9% 261 73,7% 93 26,3%
>3 845 23,7% 644 76,2% 201 23,8%
Chronic comorbidities            
Hypertension 487 13,7% 378 77,6% 109 22,4% <0,005
Dyslipidaemia 460 12,9% 344 74,8% 116 25,2% 0,053
Obesity 566 15,9% 399 70,5% 167 29,5% 0,792
Chronic obstructive pulmonary disease 384 10,8% 271 70,6% 113 29,4% 0,861
HCV infection 695 19,5% 520 74,8% 175 25,2% 0,012
Chronic kidney disease 223 6,3% 176 78,9% 47 21,1% 0,007
Chronic ischaemic heart disease 60 1,7% 45 75,0% 15 25,0% 0,486
Diabetes 321 9% 203 71,7% 91 28,3% 0,774

HTX = heterosexual. IDU = injecting drug user. CDC clinical category for VIH symptoms. Catergory A = asymptomatic. Categroy B/C = Symptomatic. MSM = men who have sex with men. VL = viral load. P-value for categorical variables referes to chi-square test, and for continuous variables to the Mann-Whitney U test.

At the end of follow-up, the median CD4 cell count was 783 cells/uL (IQR 550–1061). Only 100 (2,82%) patients presented a count lower than 200 cells/uL. HIV-RNA in plasma was undetectable in 3328 (93,3%) patients. A total of 3518 (98,6%) patients were on ART, 2168 (60,77%) of them using a tenofovir-based regimen.

SARS-CoV-2 infection risk factors

From 1st January 2020 until 31st March 2022, the incidence rate of SARS-CoV-2 infection among PLWH in our cohort was 153,24 cases per 1000 person-year, with a total number of 1036 (29%) affected patients. During 2020 the incidence was 105,62 cases per 1000 person-year, in 2021 135,21 cases per 1000 person-year, and in 2022 (until March) there were 469,60 cases per 1000 person-year (Table 2). Considering the six SARS-CoV-2 waves, 422 (40,7%) of our cases occurred during the time overlapping Omicron wave, which predominance started in early December 2021.

Table 2. Incidence rates for primoinfection with SARS-CoV-2 during different period times.

Inicidence of Sars-CoV-2 priminfection
Period Cases Time person-day Inc. 1000 person-day Inc. 1000 person-year cumulative inc. (%)
Total 1036 2.467.550,00 0,420 153,245 29,04
2020 335 1.157.644,00 0,289 105,624 9,85
2021 398 1.074.393,00 0,370 135,211 12,38
2022 303 235.510,00 1,287 469,598 12,125

Time person-day considers the days each individium was in the study during the period. Inc. = incidence

The cumulative incidence of SARS-CoV-2 primoinfection in our cohort was 28,3% in men, with no significance difference in women (p-value >0,05). The median age of SARS-CoV-2 infected patients was 49 years (IQR 41–57), whereas the median age of non-infected patients was 52 years (IQR 45–59), being significantly different (p-value <0,005).

A comparison of the unadjusted and the adjusted multivariable analysis is shown in Table 3. The unadjusted analysis showed differences according to age, place of birth, HIV transmission route, tobacco use, CDC category, modified Charlson Index, detectable VL at any point during the study period and vaccination regimen. The comorbidities which were associated with a greater risk of infection were hypertension, dyslipidemia, HCV infection and chronic ischemic heart disease. However, in the adjusted multivariable analysis only MSM was associated with an increased risk of SARS-CoV-2 infection, while African origin, tobacco use and complete or booster vaccination regimen remained negatively associated with SARS-CoV-2 infection.

Table 3. Factors associated with SARS-CoV-2 infection.

SARS-CoV-2 diagnosis
  HR (N = 3567) (95% CI) p-value aHR (N = 3497) (95% CI) p-value
Sex      
Male ref    
Female 1,134 (0,984–1,305) 0,082      
Age, years        
<35 ref ref
36–50 0,645 (0,533–0,782) 0,0001 0,917 (0,745–1,129) 0,413
51–65 0,441 (0,364–0,534) 0,0001 0,847 (0,675–1,062) 0,151
66–80 0,354 (0,26–0,482) 0,0001 0,847 (0,601–1,193) 0,341
80–95 0,316 (0,129–0,77) 0,011 0,542 (0,217–1,353) 0,189
Place of birth  
Europe ref ref
Africa 0,678 (0,444–1,035) 0,072 0,457 (0,292–0,714) 0,001
South America 1,536 (1,305–1,807) 0,0001 1,052 (0,883–1,254) 0,57
Others 0,39 (0,126–1,212) 0,104 0,296 (0,095–0,921) 0,036
HIV transmission route          
HTX ref ref
IDU 0,851 (0,709–1,022) 0,084 0,923 (0,759–1,124) 0,425
MSM 1,282 (1,111–1,479) 0,001 1,324 (1,138–1,54) <0,0005
others 1,355 (0,842–2,179) 0,211 1,026 (0,606–1,737) 0,925
unknown 0,958 (0,696–1) 0,792 0,979 (0,7–1,37) 0,902
Tobacco use  
Non-smoker ref 0,052 ref
Smoker 0,848 (0,74–0,972) 0,018 0,802 (0,665–0,967) 0,021
Ex-smoker 0,984 (0,749–1,068) 0,218 0,747 (0,614–0,908) 0,003
Tobacco use
Non-smoker ref    
Ever-smoker 0,863 (0,763–0,957) 0,018    
CDC clinical category          
Category A ref ref
Category B / C 0,773 (0,679–0,88) 0,00001 1,024 (0,853–1,229) 0,798
Modified Charlson Index
0–1 ref ref
2–3 0,778 (0,627–0,965) 0,023 1,124 (0,884–1,429) 0,341
>3 0,685 (0,586–0,801) 0,0001 0,849 (0,685–1,052) 0,135
CD4/CD8 before infection or end of study period
<0.8 ref
0.8–1 0,886 (0,731–1,075) 0,22    
>1 1,034 (0,895–1,194) 0,651    
VL>50 before infection or end of study period
No ref ref
Yes 1,108 (0,86–1,427) 0,427 0,799 (0,588–1,086) 0,152
VL detectable at any point during the study period
No ref ref
Yes 1,251 (1,073–1,459) 0,004 1,152 (0,956–1,387) 0,136
Tenofovir-based regimen
No ref ref
Yes 1,08 (0,952–1,226) 0,231 0,999 (0,878–1,137) 0,99
Vaccionation regimen before infection or end of study period
Unvaccinated or incomplete ref ref
Complete 0,379 (0,33–0,434) 0 0,359 (0,312–0,412) <0,0005
Booster 0,08 0,065–0,098 0 0,077 (0,062–0,095) <0,0005
CD4 cell count (cells per uL)
<200 ref
200–349 0,744 (0,477–1,16) 0,192    
350–500 0,743 (0,49–1,1279 0,162    
>500 0,899 (0,621–1,301) 0,572    
CD4 <200 cell
Yes ref ref
No 0,871 (0,602–1,26) 0,472 0,793 (0,532–1,181) 0,253
Chronic comorbidities
Hypertension 0,028 (0,02–0,039) 0    
Dyslipidaemia 0,788 (0,65–0,956) 0,016    
Obesity 1,023 (0,867–1,207) 0,79    
Chronic obstructive pulmonary disease 0,997 (0,82–1,212) 0,974    
HCV infection 0,762 (0,648–0,896) 0,001    
Chronic kidney disease 0,648 (0,483–0,868) 0,004    
Chronic ischaemic heart disease 0,807 (0,485–1,344) 0,41    
Diabetes 0,939 (0,758–1,165) 0,569      

HRs were calculated using Cox proportional hazards models. HR = hazard ratio. HTX = heterosexual. IDU = injecting drug user. CDC clinical category for VIH symptoms. Catergory A = asymptomatic. Categroy B/C = Symptomatic. MSM = men who have sex with men. VL = viral load. aHR = adjusted hazard ratio.

Eighteen (1,73%) patients required hospitalization because of COVID19 infection. Most of these patients had a mild-moderate infection, whereas only 2 of them required intensive care unit admission. Two out of 18 patients died because of SARS-CoV-2 infection.

SARS-CoV-2 vaccination coverage

Taking all the study period into account, 722 (20,24%) patients received no vaccines or an incomplete regimen, whereas 2845 (79,75%) patients presented a complete vaccination status or received a booster. Differences regarding vaccination coverage are shown in Table 4. It is worth noticing that vaccination coverage was lower among female, people from Africa and South America, as well as in those patients with a previous SARS-CoV-2 diagnosis, although none of them remained statistically significant in the adjusted multivariable analysis. On the other hand, vaccination coverage was higher among older age groups, among those with a Charlson Index score of 2–3 points, in MSM and among tobacco users.

Table 4. Factors associated with SARS-CoV-2 vaccine coverage among PLWH.

SARS-CoV-2 vaccine coverage
Total No vaccine/Incomplete Status (N = 722) Complete/Booster Status (N = 2845) p-value OR 95% CI p -value aOR 95% CI p -value
Birth place
Europe 2930 551 18,8% 2379 81,2% <0,0005 ref ref
  Africa 117 38 32,5% 79 67,5% 0,482 (0,323–0,717) <0,0005 0,685 0,447–1,05 0,685
  South-America 493 126 25,6% 367 74,4% 0,675 (0,54–0,843) 0,001 0,896 0,703–1,141 0,372
  Other 26 7 26,9% 19 73,1% 0,692 (0,263–1,503) 0,297 0,883 0,359–2,17 0,786
Sex
Female 809 196 24,2% 613 75,8% 0,001 0,737 (0,611–0,888) 0,001 0,844 0,675–10,54 0,135
  Male 2758 526 19,1% 2232 80,9% ref ref
Age (15 year intervals) (missing 1)
<35 336 122 36,3% 214 63,7% <0,0005 ref ref
36–50 1260 286 22,7% 974 77,3% 0,739 (0,314–1,737) 0,487 2,088 1,587–2,749 <0,0005
  51–65 1666 278 16,7% 1388 83,3% 1,434 (0,621–3,310) 0,398 3,062 2,276–4,120 <0,0005
  66–80 277 28 10,1% 249 89,9% 2,102 (0,911–4,85) 0,082 5,122 3,17–8,288 <0,0005
  81–95 27 8 29,6% 19 70,4% 3,744 (1,52–9,337) 0,04 1,346 0,555–3,261 0,511
HIV transmission route
HTX 1121 257 22,9% 864 77,1% 0,064 ref ref
  IDU 747 141 18,9% 606 81,1% 1,278 (1,016–1,609) 0,036 0,922 0,714–1,191 0,533
  MSM 1484 279 18,8% 1205 81,2% 1,285 (1,062–1,555) 0,01 1,381 1,093–1,745 0,007
  others 50 13 26,0% 37 74,0% 0,847 (0,442–1,617) 0,614 1,622 0,816–3,226 0,168
  unknown 165 32 19,4% 133 80,6% 1,236 (0,82–1,863) 0,311 1,157 00,756–1,771 0,501
Tobacco Use
Non- Smoker 1847 424 23,0% 1423 77,0% <0,0005 ref ref
  Ever smoker 1720 298 17,3% 1422 82,7% 1,422 (1,205–1,678) <0,0005 1,235 1,035–1,475 0,02
HIV symptomatic
Asymptomatic (category A) 2259 479 21,2% 1780 78,8% 0,06 ref ref
  Sympotmatic (category B/C) 1308 243 18,6% 1065 81,4% 1,179 (0,993–1,401) 0,06 0,999 0,784–1,273 0,999
Tenofovir based treatment
No 1350 274 20,3% 1076 79,7% 0,999 ref ref
  Yes 2168 440 20,3% 1728 79,7% 1 (0,845–1,184) 0,999
Chronic comorbidities (referenced to no comorbility condition)
Obesity 566 89 15,7% 477 84,3% 0,004 1,433 (1,124–1,826) 0,004
  Hypertension 487 63 12,9% 424 87,1% <0,0005 1,832 (1,287–2,42) <0,0005
  Dyslipidaemia 460 55 12,0% 405 88,0% <0,0005 2,013 (1,5–2,702) <0,0005
  Chronic ischaemic heart disease 60 6 10,0% 54 90,0% 0,046 2,309 (0,989–5,388) 0,053
  Chronic obstructive pulmonary disease 384 66 17,2% 318 82,8% 0,115 1,251 (0,947–1,653) 0,116
  Chronic liver disease 33 9 27,3% 24 72,7% 0,312 0,674 (0,312–1,456) 0,316
  Diabetes 321 44 13,7% 277 86,3% 0,002 1,662 (1,196–2,31) 0,002
  Chronic kidney disease 223 28 12,6% 195 87,4% 0,003 1,824 (1,217–2,734) 0,004
  HCV infection 695 126 18,1% 569 81,9% 0,123 1,183 (0,956–1,463) 0,123
  HBV infection 85 16 18,8% 69 81,2% 0,742 1,097 (0,633–1,901) 0,742
  Neuropsychiatric disease 204 33 16,2% 171 83,8% 0,137 1,335 (0,911–1,956) 0,138
Charlson Index
0–1 2368 518 21,9% 1850 78,1% <0,0005 ref ref
  2–3 354 46 13,0% 308 87,0% 1,875 (1,355–2,594) <0,0005 1,492 1,056–2,107 0,023
  >3 845 158 18,7% 687 81,3% 1,217 (0,998–1,485) 0,052 0,994 0,754–1,309 0,964
Prior Sars-CoV-2 infection
No 3022 525 17,4% 2497 82,6% <0,0005 ref
  Yes 545 197 36,1% 348 63,9% 0,371 (0,305–0,453) <0,0005

A total of 1929 (61,37%) patients received Pfizer-Biontech vaccine as their first dose, 543 (17,27%) patients received Moderna, 369 (12,19%) Astrazeneca, 295 (11,74%) Janssen and 7 received other than the previous stated. Booster vaccinations were predominantly done with Moderna (75,51%) or Pfizer (20,59%).

The incidence rate of SARS-CoV-2 infection was 103,24 cases per 1000 person-year in the period before an available vaccine. On the other hand, the incidence rate of SARS-CoV-2 infection was 131,73 cases per 1000 person-year in those without vaccine, 141,89 cases per 1.000 person-year with incomplete vaccination status, 116,69 cases per 1.000 person-year with complete vaccination status and 65,50 cases per 1000 person-year with booster status (Table 5).

Table 5. Incidence rate of SARS-CoV-2 in relation with the different vaccine status covered.

SARS-CoV-2 primoinfection incidence
Status Cases Time (person-day) Incidence (1000 person-day) Incidence (1000 person-year)
Infection prior available vaccines 324 1144672 0,283 103,249
Without vaccine 222 615101 0,361 131,734
Incomplete Status 291 748569 0,389 141,891
Complete Status 303 947710 0,320 116,697
Booster status 118 657530 0,179 65,503

Time was considered from the moment vaccines were available until the moment of infection for every person.

Discussion

Our study showed that SARS-CoV-2 infection was more frequent among MSM, while African origin, tobacco use and vaccination were negatively associated with SARS-CoV-2 diagnosis. When we analyzed COVID-19 vaccination coverage, older patients and those with more comorbidities had received more doses of vaccine, which probably explains why we found a negative association between these variables and SARS-CoV-2 infection in the unadjusted analysis but not in the adjusted multivariable analysis, highlighting the protective effect of vaccination.

The incidence of SARS-CoV-2 infection among PLWH has been variable across Europe, ranging from 0,3% to 5,7% person years [4]. However, most of this studies refer to the beginning of the pandemic, with little published information about the actual situation. Rial-Crestelo et. al. [17] reported an infection rate of 6,74%, with data from a tertiary hospital in Madrid (Spain) until February 2021. As far as we know, this is the first study to evaluate the COVID-19 impact among PLWH during such a long time period. The incidence of SARS-CoV-2 infection in our cohort was 153 cases per 1000 person years (29,04%). Considering the omicron wave start (December 2021), 422 (40,7%) of the infections were diagnosed in this period. Another factor that increases as much the infection number could be the widespread use of antigen tests, which were more accessible and could let to more diagnosis.

According to the Ministry of Health of the Balearic Islands, a total of 268.310 SARS-CoV-2 confirmed cases were reported from January 2020 until March 2022 in the general population [3]. This represents an approximate rate of 101,6 cases per 1.000 person years, lower than the incidence reported among PLWH in our cohort. Different results have been described in other cohorts. Fernández-Fuentes et. al. [18] showed a lower seroincidence of SARS-CoV-2 infection among PLWH from May to November 2020 in Seville, pointing out that a possible explanation could be a higher compliance of preventing measures. Other reports also performed mainly during the first year of the pandemic found similar results, with lower SARS-CoV-2 incidence among PLWH [17, 19, 20]. On the other hand, Nomah et. al. [21] reported less SARS-CoV-2 testing among PLWH from March to December 2020 in Catalonia but with a higher test positivity compared with general HIV-negative population.

Our study includes the introduction of SARS-CoV-2 vaccination in December 2021. By March 2022, 86,2% of the general population had complete status of vaccination in Majorca [3], whereas only 79,75% of our cohort had achieved it. There are several hypothetical explanations that account for this difference. Firstly, it could be attributed to a certain reluctance to SARS-CoV-2 vaccination among PLWH. Socioeconomic differences and education level may have also influenced. In addition, PLWH were not considered a priority group for the Spanish authorities during the immunization campaign until October 2021, when only PLWH with CD4 count less than 200/uL were included [15].

Some studies have analyzed factors associated with SARS-CoV-2 vaccination coverage among PLWH. Similar to Nomah et. al. [22], we found that being from outside of Europe and having a previous SARS-CoV-2 infection were associated with a lower vaccination coverage, although only in the unadjusted analysis; whereas the vaccine uptake increased with increasing age groups and increasing number of comorbidities. Nomah et. al. [22] also showed that CD4 cell count of 200-349/uL or 350-499/uL and detectable plasma HIV-RNA were associated with less vaccination. Contrary to us, Lv et. al. [23] described lower vaccination rates related to the presence of chronic disease and also to CD4 T cell count <200/uL. Jaiswal et. al. [24] also showed that vaccine uptake was associated with older age, higher education level and undetectable viral load.

It is worth noticing that a reduced risk of SARS-CoV-2 infection was observed in our study among those patients with any dose of SARS-CoV-2 vaccine, particularly in those with complete or booster vaccination. Increasing data regarding immunogenicity and safety of SARS-CoV-2 vaccines among PLWH is being published. Initially, it was hypothesized that the humoral response could be reduced as a result of a dysfunctional immune system. However, several studies have shown that SARS-CoV-2 vaccines among PLWH are acceptable, with a safe profile and an optimal immune response, especially in those cases on established ART, suppressed HIV viral load and high baseline CD4 counts [25, 26]. Fowokan et. al. [27] described that PLWH reached the vaccine efficacy peak later than healthy controls, with a faster waning degree over time. The third dose (booster shot) has also proven to increase antibody response among PLWH [28, 29], being of upmost importance.

In our study, co-infected patients were younger. Older age has been widely described as a risk factor for severe disease [6, 3032]. Theodore et. al. [33] reported that age >65 years was associated with a decreased rate of co-infection, suggesting stricter adherence to regulations, which is probably what happened in our cohort, with higher vaccination coverage in older age groups. Conversely, another study described older age and opportunistic infections as risk factors for coinfection [19].

We observed that being from South America or MSM were possible risk factors for SARS-CoV-2 diagnosis. These results had been also described in previous reports [10, 34]. Nevertheless, only MSM remained significant in our multivariate analyses, despite higher vaccine coverage. Other variables such as social interactions, safety distance, mask wearing, hand hygiene or proper ventilation of the rooms had also a great impact during all the pandemic. Although they could not be measured in our study, these variables might have influenced on the above results, acting as confounders. On the other hand, African origin was associated with a reduced risk of SARS-CoV-2 infection, despite presenting a low vaccination coverage in the unadjusted analysis. This result has also been described in previous reports [33]. Other studies with a higher percentage of non-Hispanic black people found opposite results [35], probably associated with socioeconomic inequities in that area. More data is needed in order to study the eventual role of ethnic groups.

There are diverging results in the literature regarding the influence of comorbidities on SARS-CoV-2 diagnosis. Some authors showed that having 4 or more comorbidities was associated with an increased risk of infection [10]. Similar to us, others studies found no significant difference [18, 34]. In our case, this could be explained by a higher vaccination coverage among people with chronic diseases, probably because of a self-perception of risk.

Tobacco use showed unexpected results in our study, with smokers and ex-smokers being negatively associated with SARS-CoV-2 infection. It is generally known that cigarette smoking is a risk factor for respiratory infectious diseases. Therefore, one possible explanation to our results could be a higher vaccination uptake among these patients because of a sense of vulnerability. However, Fernández-Fuentes et. al. published similar results during de pre-vaccination period [18]. Despite possible biases, several hypothesis to explain both the protective and the harmful effect of tobacco use on SARS-CoV-2 infection have been published [36]. In any case, further investigation is still needed.

Shortly after the beginning of the pandemic, tenofovir was proposed as a promising treatment for COVID-19 [37, 38]. Some studies have shown lower severity of SARS-CoV-2 infection in PLWH treated with tenofovir [3941]. Lea et. al. [41] described that the protective effect of tenofovir alafenamide (TAF) and tenofovir disoproxil fumarate (TDF) were similar in magnitude. However, other reports didn’t show a clinical benefit after adjusting for specific comorbidities, mainly chronic kidney disease [42, 43]. The PANCOVID study also showed no evidence that treatment with TDF and emtricitabine (FTC) improves outcomes among hospitalized patients [44]. In our study, tenofovir-based ART had no influence on the risk of SARS-CoV-2 infection. CD4 count or HIV viral load didn’t show any association with SARS-CoV-2 infection either, in line with the previously mentioned studies [10, 18].

This study has some limitations. First of all, the first case of SARS-CoV-2 infection in the Balearic Islands was reported on 7th February 2020. Therefore, we have probably overestimated the period of time at risk of SARS-CoV-2 infection and the period of time without vaccines. Second, as this is a retrospective study, data was not collected for analyses proposes. In line with this, hospitalized patients are probably underestimated because secondary diagnosis such as HIV were not fully registered at that time. In addition, 322 people entered our cohort after 1st January 2022. Some of them were new HIV diagnoses, but others were PLWH already diagnosed who came from other autonomous communities or from other countries. In these cases, there was a lack of information from the previous study period which could let to an underdiagnoses of SARS-CoV-2 infection. Third, incidence and vaccination coverage comparisons between general population and PLWH included in the EVHIA were not standardized. Finally, most of the PLWH included in this study were on effective ART and, therefore, results can’t be generalized.

Conclusions

To sum up, no HIV related factor was associated with an increased risk of SARS-CoV-2 infection in our study, except for differences in the transmission route. Possible confounding variables such as mask wearing or social interactions could not be measured. Conversely, African origin and vaccination were associated with a reduced risk of infection, highlighting the importance of immunization in the control of SARS-CoV-2 infection. Vaccination coverage in our cohort was higher among older people and those with a higher number of comorbidities, who were considered priority groups. However, more emphasis should be placed on those groups with less vaccination coverage.

Acknowledgments

The authors thank the study participants and their families; site staff who provide healthcare assistance; and programmer analysts who constantly update the EVIHA platform. They also have a special acknowledgement for Aina Millan, from the Clinical Research and Clinical Trials Unit (UICEC), Idisba.

Data Availability

Data cannot be shared publicly because of legal considerations. According to the protocol approved by the Ethics Committee (IB 3808/18 PI) and the informed consent signed by all participants, data transfer to third parties is not allowed due to patient confidentiality. Data are available from the Idisba Data Access Committee (contact via email helemh.vilchez@ssib.es) for researchers who meet the criteria for access to confidential data.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Jake M Pry

29 Apr 2024

PONE-D-23-43118Factors associated with SARS-CoV-2 infection among people living with HIV: Data from the Balearic cohort (EVHIA)

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: 1- Line 44-47: “Older people and those with more comorbidities had higher vaccination uptake after the multivariable analysis; whereas females, African and South American people, and prior SARS-CoV-2 infection were associated with less vaccination coverage only in the unadjusted analysis”. These are not the main results in the present study. The authors should focus on to explore the risk factors (such as age, comorbidities, vaccination, etc.) modulating the infection of SARS-CoV-2 by multivariable analysis.

2- Line 57-58: “The Balearic Islands reported 268.000 SARS-CoV-2 confirmed cases and more than 1.300 deaths during these six waves”. The authors should check whether the number of SARS-CoV-2 confirmed cases and deaths was correct.

3- In Table 3, would the authors please check whether aHZR is right.

4- Other variables (such as social interactions, mask wearing, etc.) should be considered when the authors explored the risk factors associated with SARS-CoV-2 infection among people living with HIV.

5- Would the authors please discuss the point of MSM being a risk factor for SARS-CoV-2 infection in the section of discussion. In Table 3, the authors observed MSM was an independent risk factor for SARS-CoV-2 infection, but in Table 4, the rate of vaccination coverage was the highest among HIV transmission routes. The authors should address this.

6- There are some typographical or grammatical errors in the present manuscript, would the authors please correct.

Reviewer #2: 1. The method section stated that the paper is a descriptive retrospective study, however, I think your study is analytic.

2. In Table 3 aHZR should be replaced by aHR.

3. in case of citing more than one reference in the text, please insert all citations in Parentheses for example (5, 6) no (5)(6).

4. In Table 1, the authors reported column percentages, however, I think row percentages can be more informative.

5. The authors covered two research questions of COVID-19 incidence and vaccine coverage among PLHIV. I think the authors presented a lot of information in the manuscript; I suggest you present these two research questions in different manuscripts.

Reviewer #3: 1. This study describes a large cohort of HIV+ patients over 2 years to determine incidence and risk factors for sars cov2 infection. Data taken from an established data base with informed consent. 96% patients remained in the cohort at the end of the study period (3411).

The questions set out are investigated and answered well for the purpose of this manuscript .

A few comments:

3. Table 1 : what is p value referring to? eg age; origin and transmission

4. interesting that COPD is not a risk factor is there any data re Lung function in this cohort?

5. Are there any data re patients using HCV drugs?

4.There are other arv therapies which are thought to have sars-cov 2 activity. eg Abacavir and zidovudine and Protease inhibitors. Maybe include a comment or reference to this. Especially for those patients who were on 2nd / 3rd line regimens , and for patients with vl>50

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

**********

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Attachment

Submitted filename: Comments.docx

pone.0308568.s001.docx (13.9KB, docx)
PLoS One. 2024 Aug 7;19(8):e0308568. doi: 10.1371/journal.pone.0308568.r002

Author response to Decision Letter 0


12 Jun 2024

Dear Editor and Reviewers,

Thank you very much for taking the time to review our manuscript and for providing constructive feedback. It is a pleasure for us to have the opportunity to improve it. We have carefully read your valuable suggestions and comments, and we have thoroughly revised the manuscript accordingly. Please see below, in blue, our detailed responses and concerns.

ACADEMIC EDITOR’S COMMENTS

There is controversy regarding the effect of COVID-19 infection on people living with HIV, so the impact of SARS-CoV-2 infection among people living with HIV (PLWH) has been a matter of research. In this study the authors calculated COVID-19 incidence and related factors among PLWH, also they evaluated vaccine coverage and related factors among PLWH. The results showed that the incidence of COVID-19 among PLWH was 153 cases per 1000 person-years which was more than the general population. Also, they showed that Men who have sex with men (MSM) were associated with an increased risk of SARS-CoV-2 infection, whereas African origin, tobacco use, and complete or booster vaccination coverage were negatively related to SARS-CoV-2 infection among PLWH. I think this is a valuable study, however, I have some minor comments:

1. The method section stated that the paper is a descriptive retrospective study, however, I think your study is analytic: Suggestion has been accepted and changed.

2. In Table 3 aHZR should be replaced by aHR. : Correction done.

3. In case of citing more than one reference in the text, please insert all citations in Parentheses for example (5, 6) no (5)(6). Correction done.

4. In Table 1, the authors reported column percentages, however, I think row percentages can be more informative: Thank you for the suggestion. We also consider it is more informative and have therefore adapted the suggestion.

5. The authors covered two research questions of COVID-19 incidence and vaccine coverage among PLHIV. I think the authors presented a lot of information in the manuscript; I suggest you present these two research questions in different manuscripts. We really appreciate your suggestion. We decided to present the two questions in the same manuscript because both issues are related, since vaccination coverage had a great influence on the decrease of COVID-19 cases. Therefore, we found it interesting to analyze which factors were associated with vaccination. We completely agree that there is a lot of information on display. Therefore, changes have been made to focus on these two main questions and to avoid too much additional information.

REVIEWERS' COMMENTS

Reviewer #1:

1- Line 44-47: “Older people and those with more comorbidities had higher vaccination uptake after the multivariable analysis; whereas females, African and South American people, and prior SARS-CoV-2 infection were associated with less vaccination coverage only in the unadjusted analysis”. These are not the main results in the present study. The authors should focus on to explore the risk factors (such as age, comorbidities, vaccination, etc.) modulating the infection of SARS-CoV-2 by multivariable analysis. We are grateful for this comment as it has helped us to summarize better our findings. We had two main objectives: 1) to evaluate the incidence and factors associated with SARS-CoV-2 diagnosis among PLWH, and 2) to assess factors related to vaccination coverage.

Vaccination had a great impact reducing SARS-CoV-2 infection. That is why we thought that analyzing factors associated with vaccination in the same article could be interesting. Appropriate corrections have been made. Unnecessary information has been removed.

2- Line 57-58: “The Balearic Islands reported 268.000 SARS-CoV-2 confirmed cases and more than 1.300 deaths during these six waves”. The authors should check whether the number of SARS-CoV-2 confirmed cases and deaths was correct. This information is correct, the reference is from the official webpage from the Balearic Islands Government. Our Autonomous Community had fewer cases of SARS-CoV-2 infection than other areas of Spain. This is probably why the mortality rate was not so high.

3- In Table 3, would the authors please check whether aHZR is right. Thank you for the comment, the second column refers to the adjusted Hazard Ratio. Z has been deleted from the acronym.

4- Other variables (such as social interactions, mask wearing, etc.) should be considered when the authors explored the risk factors associated with SARS-CoV-2 infection among people living with HIV. We absolutely agree with the reviewer. Variables such as social interactions, safety distance, mask wearing, hand hygiene or proper ventilation of the rooms had a great impact during all the pandemic. Unfortunately, we have no way to measure them. We have added a specific mention about this issue in the new manuscript.

5- Would the authors please discuss the point of MSM being a risk factor for SARS-CoV-2 infection in the section of discussion? In Table 3, the authors observed MSM was an independent risk factor for SARS-CoV-2 infection, but in Table 4, the rate of vaccination coverage was the highest among HIV transmission routes. The authors should address this. Thank you very much for your comment. This point is probably related with the previous one. Social interactions or mask wearing could not be measured in our study and, in this case, they probably acted as confounding variables that generated an association between MSM and SARS-CoV-2 infection. We have clarified this issue in the new manuscript.

6- There are some typographical or grammatical errors in the present manuscript, would the authors please correct. We regret any careless errors in the manuscript. We have already tried to correct them all.

Reviewer #2:

1. The method section stated that the paper is a descriptive retrospective study, however, I think your study is analytic. Suggestion has been accepted and changed.

2. In Table 3 aHZR should be replaced by aHR. Thank you for the comment, the second column referes to the adjusted Hazard Ratio. Z has been deleted from the acronym.

3. in case of citing more than one reference in the text, please insert all citations in Parentheses for example (5, 6) no (5)(6). Correction done.

4. In Table 1, the authors reported column percentages, however, I think row percentages can be more informative. Thank you for the suggestion. We also consider it is more informative and have therefore adapted the suggestion.

5. The authors covered two research questions of COVID-19 incidence and vaccine coverage among PLHIV. I think the authors presented a lot of information in the manuscript; I suggest you present these two research questions in different manuscripts. We really appreciate your suggestion. We decided to present the two questions in the same manuscript because both issues are related, since vaccination coverage had a great influence on the decrease of COVID-19 cases. Therefore, we found it interesting to analyze which factors were associated with vaccination. We completely agree that there is a lot of information on display. Therefore, changes have been made to focus on these two main questions and to avoid too much additional information.

Reviewer #3:

1. This study describes a large cohort of HIV+ patients over 2 years to determine incidence and risk factors for sars cov2 infection. Data taken from an established data base with informed consent. 96% patients remained in the cohort at the end of the study period (3411). The questions set out are investigated and answered well for the purpose of this manuscript. A few comments:

3. Table 1 : what is p value referring to? eg age; origin and transmission – P-value of table 1 refers to chi square in categorical variables and Mann-Whintey U test in continues.

4. interesting that COPD is not a risk factor is there any data re Lung function in this cohort? All patients in our cohort with a diagnosis of COPD have respiratory function tests that support this diagnosis.

5. Are there any data re patients using HCV drugs? Thank you very much for your interest in our cohort. A total of 28 patients received HCV drugs during the study period. However, we did not analyze their association with SARS-CoV-2 infection.

4. There are other arv therapies which are thought to have sars-cov 2 activity. eg Abacavir and zidovudine and Protease inhibitors. Maybe include a comment or reference to this. Especially for those patients who were on 2nd / 3rd line regimens, and for patients with vl>50. Thank you for pointing this out. We have considered your suggestion and some new references have been included in the introduction. However, as we only analyzed the association between SARS-CoV-2 and tenofovir, we have not discussed other antiretroviral drugs in order not to overextend the manuscript.

Thank you again for your attention and consideration. We hope that the revised version of the manuscript can meet your expectations. Please let us know if further improvements are needed.

Best regards,

Francisca Artigues Serra & coauthors

Attachment

Submitted filename: Response to reviewers.docx

pone.0308568.s002.docx (22.7KB, docx)

Decision Letter 1

Jake M Pry

25 Jul 2024

Factors associated with SARS-CoV-2 infection among people living with HIV: Data from the Balearic cohort (EVHIA)

PONE-D-23-43118R1

Dear Dr. Artigues Serra,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Jake M. Pry, PhD, MPH

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Many thanks for taking time and making the effort to respond thoroughly to reviewer feedback.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: (No Response)

**********

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If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

**********

Acceptance letter

Jake M Pry

29 Jul 2024

PONE-D-23-43118R1

PLOS ONE

Dear Dr. Artigues Serra,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. Jake M. Pry

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Comments.docx

    pone.0308568.s001.docx (13.9KB, docx)
    Attachment

    Submitted filename: Response to reviewers.docx

    pone.0308568.s002.docx (22.7KB, docx)

    Data Availability Statement

    Data cannot be shared publicly because of legal considerations. According to the protocol approved by the Ethics Committee (IB 3808/18 PI) and the informed consent signed by all participants, data transfer to third parties is not allowed due to patient confidentiality. Data are available from the Idisba Data Access Committee (contact via email helemh.vilchez@ssib.es) for researchers who meet the criteria for access to confidential data.


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