Literature DB >> 31009486

Herpes simplex virus type 1 epidemiology in Latin America and the Caribbean: Systematic review and meta-analytics.

Layan Sukik1,2, Maryam Alyafei1,2, Manale Harfouche1, Laith J Abu-Raddad1,3,4.   

Abstract

OBJECTIVES: To investigate the epidemiology of herpes simplex virus type 1 (HSV-1) in Latin America and the Caribbean.
METHODS: Systematic review and meta-analytics guided by the Cochrane Collaboration Handbook and reported following the PRISMA guidelines.
RESULTS: Thirty-three relevant reports were identified including 35 overall (and 95 stratified) seroprevalence measures, and five and nine proportions of virus isolation in genital ulcer disease (GUD) and in genital herpes, respectively. Pooled mean seroprevalence was 57.2% (95% CI: 49.7-64.6%) among children and 88.4% (95% CI: 85.2-91.2%) among adults. Pooled mean seroprevalence was lowest at 49.7% (95% CI: 42.8-56.6%) in those aged ≤10, followed by 77.8% (95% CI: 67.9-84.8%) in those aged 10-20, 82.8% (95% CI: 73.1-90.8%) in those aged 20-30, 92.5% (95% CI: 89.4-95.1%) in those aged 30-40, and 94.2% (95% CI: 92.7-95.5%) in those aged ≥40. Age was the strongest source of heterogeneity in seroprevalence, explaining 54% of variation. Evidence was found for seroprevalence decline over time. Pooled mean proportion of HSV-1 isolation was 0.9% (95% CI: 0.0-3.6%) in GUD and 10.9% (95% CI: 4.4-19.4%) in genital herpes.
CONCLUSIONS: HSV-1 is a widely prevalent infection in this region, but its epidemiology may be slowly transitioning, with still limited contribution for HSV-1 in genital herpes.

Entities:  

Mesh:

Year:  2019        PMID: 31009486      PMCID: PMC6476500          DOI: 10.1371/journal.pone.0215487

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Infection with herpes simplex virus type 1 (HSV-1) is prevalent globally [1]. HSV-1 is responsible for a range of mild to serious morbidities [2, 3], with its typical clinical manifestation being orolabial herpes lesions [2, 4]. The infection, lifelong and mostly asymptomatic, is usually acquired orally and in childhood [3]. However, mounting evidence suggests an HSV-1 epidemiological transition in Europe and North America [4-7] and in Asia [8], associated with decreasing oral acquisition in childhood and increasing sexual acquisition (through oral sex) in adulthood [4-6]. In multiple Western countries, HSV-1 is already the primary cause of first episode genital herpes, surpassing the role of that of HSV-2 [4, 5, 7, 9–11]. An epidemiological transition is defined here as a significant change in the occurrence of the infection and/or its mode of transmission patterns. HSV-1 infection is of growing interest and a focus of an international multi-sectorial effort, guided by the World Health Organization, to develop a vaccine to control infection transmission [12, 13]. To inform these global health efforts, we aimed in the present study to provide a detailed investigation of the epidemiology of HSV-1 in Latin America and the Caribbean, by conducting a comprehensive systematic review and a range of meta-analytics. Importantly, we estimated HSV-1 antibody prevalence (seroprevalence), its associations and temporal trend, and assessed the role of HSV-1 as a cause of clinically-diagnosed genital ulcer disease (GUD) and clinically-diagnosed genital herpes.

Material and methods

The methodology of this study was adapted from that of a study investigating HSV-1 epidemiology in Asia [8].

Data sources and search strategy

The systematic review and meta-analyses were guided by the Cochrane collaboration Handbook [14], and were reported following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines (checklist in S1 Table) [15]. PubMed, Embase, and LILACS databases were systematically searched up to September 12, 2018. The search strategies included MeSH/Emtree and broad terms with no language or year restrictions (S2 Table). The definition for the Latin America and the Caribbean region included 46 countries, as listed in S1 Box.

Study selection and inclusion and exclusion criteria

Search results were de-duplicated using a reference manager, Endnote (Thomson Reuters, USA). Titles and abstracts were screened for relevant and potentially relevant reports, and the full-texts of these relevant or potentially relevant reports were retrieved for further screening. Bibliographies of identified relevant reports and reviews were also screened for additional potentially relevant reports. Initial screening was conducted by LS and MA, and double screening was conducted by MH. Reports met the inclusion criteria if they reported primary data on any of three outcome measures: 1) HSV-1 seroprevalence based on a valid diagnostic method (i.e. strictly type-specific glycoprotein-G based assays), 2) proportion of HSV-1 virus isolation in clinically-diagnosed GUD, or 3) proportion of HSV-1 virus isolation in clinically-diagnosed genital herpes. Only measures with a sample size ≥10 were included. Case reports, editorials, letters to editors, commentaries, and reviews were excluded. HSV-1 seroprevalence measures among newborns <3 months of age were excluded, as they may reflect maternal antibodies as opposed to current infection. In this systematic review, a “report” denotes a publication reporting a relevant outcome measure, while a “study” denotes the extracted details of an outcome measure.

Data extraction and synthesis

Relevant reports were extracted by LS and MA, and double-extracted by MH. Extracted data included publication details, population characteristics, study methodology characteristics, and outcome measures. The extracted variables are listed in S2 Box. Extracted overall outcome measures for the full sample were replaced by stratified measures (if available), based on a pre-defined protocol for the stratification hierarchy, provided that the sample size in each stratum was ≥10. For HSV-1 seroprevalence measures, extracted strata were prioritized for population type (Fig 1), followed by age bracket (children (≤15 years of age) versus adults (>15 years of age)), and age group (≤10, 10–20, 20–30, 30–40, and ≥40 years of age). These age ranges were informed by the actually available age strata in extracted studies. For the proportions of HSV-1 virus isolation in GUD or in genital herpes, the stratification hierarchy included primary versus recurrent episode, followed by study site (hospital versus sexually transmitted infection clinic).
Fig 1

Population type definition and classification.

Abbreviation: HSV-1 = Herpes simplex virus type 1.

Population type definition and classification.

Abbreviation: HSV-1 = Herpes simplex virus type 1.

Quality assessment

Given the documented limitations in the sensitivity and specificity of HSV-1 serology diagnostic assays [16, 17], the validity of the type-specific diagnostic method of each study was investigated and determined in consultation with an expert advisor in HSV-1 serology, Professor Rhoda Ashley-Morrow, University of Washington, Seattle. Studies where the validity of the diagnostic method could not be confirmed, were excluded from the systematic review and meta-analytics. Informed by the Cochrane approach [14], studies with valid assays were further classified into low versus high precision based on the number of individuals tested for HSV-1 in that study (<100 versus ≥100). Moreover, studies were classified into low versus high risk of bias (ROB) using two quality domains: sampling method (probability-based versus non-probability-based sampling) and response rate (≥80% versus <80%). Studies with no information on a quality domain were classified as having an “unclear” ROB for that domain. Precision and ROB domains were included in the meta-regression analyses (as described below), to examine their associations with seroprevalence, that is the influence of the characteristics of the study methodology on observed HSV-1 seroprevalence.

Meta-analyses

Pooled means were estimated for HSV-1 seroprevalence and its relevant strata by population type, age bracket, age group, and year of publication category (<2000, 2000–2009, and 2010–2018), as well as for the proportions of HSV-1 virus isolation in GUD and in genital herpes, whenever ≥3 measures were available. The estimates were calculated in R version 3.4.1 [18] using a DerSimonian-Laird random-effects model [19], as applied in the meta package [20]. The Freeman-Tukey type arcsine square-root transformation [21] was utilized to stabilize the variance of each included measure. Forest plots were produced to visualise estimates and their 95% confidence intervals (CIs). Heterogeneity was assessed using three complementary metrics: 1) Cochrane Q statistics to test for existence of heterogeneity [19, 22], 2) I2 to provide the magnitude of heterogeneity that is explained by true differences in the outcome measures across studies (as opposed to being due to sampling variation) [19, 23], and 3) prediction interval to provide the range of true effect sizes of the outcome measures around the pooled mean [19, 23].

Meta-regressions

Associations with HSV-1 seroprevalence and sources of between-study heterogeneity were investigated using univariable and multivariable random-effects meta-regression analyses. Independent variables with a p-value ≤0.1 in univariable analysis were included in the multivariable analyses. In the multivariable models, a p-value of ≤0.05 for any given independent variable indicated strong evidence for an association with HSV-1 seroprevalence. The included independent variables were set a priori and consisted of: age bracket, age group, sex, population type, country’s income, assay type (Western blot, enzyme-linked immunosorbent assay, and others), sample size (<100 versus ≥100), sampling method (non-probability-based versus probability-based), response rate (≥80 versus otherwise), year of publication category, year of data collection, and year of publication. The variable of country’s income (for countries with available data and per World Bank classification [24]) categorized the countries into upper-middle-income countries (Brazil, Colombia, Costa Rica, Jamaica, Mexico, and Peru), high-income countries (Barbados, Chile, and Argentina), and “mixed” for studies including different countries in the study sample. Missing values for the year of data collection were imputed utilizing data for the year of publication as adjusted by the median difference between year of publication and year of data collection (for studies with non-missing data). The meta-regressions were conducted on the log-transformed proportions (with inverse-variance weighting) in Stata/SE version 13 [25], using the metareg package [26].

Results

Search results and scope of evidence

Fig 2 details the study selection process per PRISMA guidelines [15]. The search identified 4,023 citations (PubMed: 847, Embase: 1,329, and LILACS 1,847) of which duplicates were removed. Title and abstract screening yielded 367 relevant and potentially relevant reports. Full-text screening of these latter reports identified 29 reports that met the inclusion criteria. Four additional relevant reports [27-30] were identified through bibliography screening of reviews and relevant reports.
Fig 2

Flow chart of article selection for the systematic review of HSV-1 infection in Latin America and the Caribbean, per the PRISMA guidelines [15].

Abbreviation: HSV-1 = Herpes simplex virus type 1.

Flow chart of article selection for the systematic review of HSV-1 infection in Latin America and the Caribbean, per the PRISMA guidelines [15].

Abbreviation: HSV-1 = Herpes simplex virus type 1. Extracted measures included: 35 overall HSV-1 seroprevalence measures yielding 95 stratified seroprevalence measures, five proportions of viral HSV-1 isolation in GUD, and nine proportions of viral HSV-1 isolation in genital herpes. No HSV-1 seroprevalence measure was identified among clinical children populations.

Overview of HSV-1 seroprevalence

Table 1 lists the extracted stratified HSV-1 seroprevalence measures and their characteristics (number of measures (n) = 95). Most measures were from studies conducted prior to 2010 (n = 76; 80.0%), and were based on convenience samples (n = 68; 71.0%). Seroprevalence across all measures ranged between 7.7–100% with a median of 86.0% (n = 95; Table 2).
Table 1

Studies reporting HSV-1 seroprevalence in Latin America and the Caribbean.

Author, yearYear(s) of data collectionCountryStudy siteStudy designSampling methodPopulationHSV-1 serological assaySample sizeHSV-1 seroprevalence (%)
Healthy children populations (n = 19)
Clemens, 2010 [43]1996–97BrazilCommunityCSRS1–5 years old boysELISA5244.2
Clemens, 2010 [43]1996–97BrazilCommunityCSRS6–10 years old boysELISA4955.1
Clemens, 2010 [43]1996–97BrazilCommunityCSRS11–15 years old boysELISA12565.6
Clemens, 2010 [43]1996–97BrazilCommunityCSRS1–5 years old girlsELISA4738.3
Clemens, 2010 [43]1996–97BrazilCommunityCSRS6–10 years old girlsELISA5058.0
Clemens, 2010 [43]1996–97BrazilCommunityCSRS11–15 years old girlsELISA12674.6
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS1–9 years old girlsELISA25251.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS1–9 years old boysELISA26450.0
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv1–4 years old childrenELISA232a36.0
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv5–9 years old childrenELISA232a52.4
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv10–14 years old childrenELISA233a68.1
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv7–11 month babiesIF137.7
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv1–4 years old childrenIF5038.0
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv5–9 years old childrenIF5064.0
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv10–14 years old childrenIF5092.0
Robinson, 2002 [47]-Multiple countries in South AmericaCommunityCSConv≤3 years old childrenWB2329.0
Robinson, 2002 [47]-Multiple countries in South AmericaCommunityCSConv4–6 years old childrenWB5672.0
Robinson, 2002 [47]-Multiple countries in South AmericaCommunityCSConv7–9 years old childrenWB6876.0
Robinson, 2002 [47]-Multiple countries in South AmericaCommunityCSConv10–13 years old childrenWB5481.0
Healthy adult populations (n = 51)
Arriaga-Demeza, 2008 [48]2002–03MexicoCommunityCSConv18–20 years old femalesWB19550.3
Arriaga-Demeza, 2008 [48]2002–03MexicoCommunityCSConv21–25 years old femalesWB15353.6
Arriaga-Demeza, 2008 [48]2002–03MexicoCommunityCSConv≥26 years old femalesWB3174.2
Arriaga-Demeza, 2008 [48]2002–03MexicoCommunityCSConv18–20 years old malesWB10346.6
Arriaga-Demeza, 2008 [48]2002–03MexicoCommunityCSConv21–25 years old malesWB10261.8
Arriaga-Demeza, 2008 [48]2002–03MexicoCommunityCSConv≥26 years old malesWB1855.6
Morrow, 2014 [16]2000–01ArgentinaCommunityCSConvArgentinian womenWB9998.9
Morrow, 2014 [16]2000–01Costa RicaCommunityCSConvCosta Rican womenWB9892.9
Morrow, 2014 [16]2000–01MexicoCommunityCSConvMexican womenWB10098.0
Clemens, 2010 [43]1996–97BrazilCommunityCSRS16–20 years old malesELISA11969.8
Clemens, 2010 [43]1996–97BrazilCommunityCSRS21–30 years old malesELISA10776.6
Clemens, 2010 [43]1996–97BrazilCommunityCSRS31–40 years old malesELISA7885.9
Clemens, 2010 [43]1996–97BrazilCommunityCSRS16–20 years old femalesELISA12875.8
Clemens, 2010 [43]1996–97BrazilCommunityCSRS21–30 years old femalesELISA12681.0
Clemens, 2010 [43]1996–97BrazilCommunityCSRS31–40 years old femalesELISA8281.7
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS20–29 years old femalesELISA252a78.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS30–39 years old femalesELISA252a96.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS40–49 years old femaleELISA252a91.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS50–59 years old femalesELISA252a98.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS≥60 years old femalesELISA252a95.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS20–29 years old malesELISA264a91.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS30–39 years old malesELISA264a91.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS40–49 years old maleELISA264a93.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS50–59 years old malesELISA264a95.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS≥60 years old malesELISA264a94.0
Corona, 2010 [28]2002–05MexicoCommunityCSConv≥ 26 years old studentsELISA5972.9
Corona, 2010 [28]2002–05MexicoCommunityCSConv21–25 years old studentsELISA41259.7
Corona, 2010 [28]2002–05MexicoCommunityCSConv18–20 years old studentsELISA33550.1
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv15–19 years old adultsELISA14683.3
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv20–29 years old adultsELISA147a83.6
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv30–34 years old adultsELISA147a95.2
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv35–39 years old adultsELISA147a92.9
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv40–44 years old adultsELISA147a96.0
Cowan, 2003 [45]-BrazilOutpatient clinicCSConv≥45 years old adultsELISA147a94.6
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv15–19 years old adultsIF5090.0
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv20–24 years old adultsIF5084.0
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv25–29 years old adultsIF5086.0
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv30–34 years old adultsIF6098.3
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv35–39 years old adultsIF5090.0
De Salles-Gomes, 1981 [46]1980BrazilOutpatient clinicCSConv≥40 years old adultsIF5096.0
Evans, 1974 [49]-BrazilOutpatient clinicCCCConvHealthy adultsIF2687.5
Jimemez, 1979 [50]-Costa RicaOutpatient clinicCSConv≥18 years old studentsNAb1650.0
Levett, 2005 [51]-BarbadosOutpatient clinicCSConvBlood donorsELISA18481.0
Levett, 2005 [51]-BarbadosOutpatient clinicCSConvAnte-natal clinic attendeesELISA12283.6
Lupi, 2011 [52]1996–97BrazilOutpatient clinicCohortbConvBlood donorsELISA15568.0
Oberle, 1989 [53]1984–85Costa RicaCommunityCSMCS≥25 years old femalesMAb76697.1
Patnaik, 2007 [54]1985–97PeruCommunityCSConvPeruvian womenWB17191.8
Patnaik, 2007 [54]1985–97ColombiaCommunityCSConvColombian womenWB6589.2
Prabhakar, 1984 [55]-JamaicaHospitalCCCConvHealthy Jamaican womenNAb6038.3
Smith, 2002 [29]1996–97PeruHospitalCCCConvHealthy Peruvian womenWB17191.8
Smith, 2002 [29]1985–88ColombiaCommunityCCCConvHealthy Colombian womenWB6589.2
Healthy age-mixed populations (n = 2)
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS10–19 years old femalesELISA25270.0
Conde-Glez, 2013 [44]2005–06MexicoCommunityCSRS10–19 years old malesELISA26471.0
Clinical adult populations (n = 7)
Calderon, 2018 [56]2014–15PeruOutpatient clinicCSConvWomen with breast cancerELISA4488.6
Evans, 1974 [49]-BrazilOutpatient clinicCCCConvPatients with Hodgkin’s diseaseIF2684.4
Moreira, 2018 [57]2015–16BrazilOutpatient clinicCCCConvWomen from a highly ZIKV-affected regionWB3293.8
Moreira, 2018 [57]2015–16BrazilOutpatient clinicCCCConvWomen from a highly ZIKV-affected regionWB16095.0
Smith, 2002 [29]1996–97PeruHospitalCCCConvWomen with squamous-cell carcinomaWB16691.5
Smith, 2002 [29]1996–97PeruHospitalCCCConvWomen with adeno-squamous carcinomaWB24100
Smith, 2002 [29]1985–88ColombiaHospitalCCCConvWomen with squamous-cell carcinomaWB7874.4
Other populations (n = 16)
Levett, 2005 [51]-BarbadosOutpatient clinicCSConvHIV-positive adultsELISA12089.2
Luchsinger, 2010 [58]2005–06ChileOutpatient clinicCSConvHIV-positive adultsELISA40092.2
Boulos, 1992 [59]-HaitiOutpatient clinicCSConvHealthy/clinical womenELISA22896.9
Conde-Glez, 1999 [60]1992MexicoOutpatient clinicCSConv16–22 years old FSWsWB30292.7
Conde-Glez, 1999 [60]1992MexicoOutpatient clinicCSConv23–27 years old FSWsWB33093.1
Conde-Glez, 1999 [60]1992MexicoOutpatient clinicCSConv28–32 years old FSWsWB18794.7
Conde-Glez, 1999 [60]1992MexicoOutpatient clinicCSConv33–37 years old FSWsWB10194.1
Conde-Glez, 1999 [60]1992MexicoOutpatient clinicCSConv>37 years old FSWsWB77100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv14–15 years old FSWsNAb15100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv16–17 years old FSWsNAb56100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv18–19 years old FSWsNAb43100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv20–21 years old FSWsNAb34100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv22–25 years old FSWsNAb46100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv26–35 years old FSWsNAb95100
Duenas, 1972 [61]-ColombiaOutpatient clinicCSConv≥36 years old FSWsNAb54100
Lupi, 2011 [52]1996–97BrazilHospitalCohortbConvMen who have sex with menELISA17085.0

a Study included sample size only for the total sample, but not for the strata. Each stratum sample size was set at total sample size divided by the number of strata.

b The original study design of the study is prospective cohort. The included seroprevalence measures are those for the baseline measures at the onset of the study, before start of follow-up.

c The original study design of the study is case-control. The included seroprevalence measures are those for each of cases and controls, separately. The population type classification was assigned based on the actual population type for each of cases and controls, separately.

Abbreviations: Conv = Convenience, CS = Cross-sectional, CC = Case-control, ELISA = Enzyme-linked immunosorbent type-specific assay, FSWs = Female sex workers, HIV = Human immunodeficiency virus, HSV-1 = Herpes simplex virus type 1, IF = Indirect immunofluorescence, MAb = Monoclonal antibody, MCS = Multistage cluster sampling, NAb = Neutralizing antibody, RS = Random sampling, WB = Western blot, ZIKV = Zika virus.

Table 2

Pooled mean estimates for HSV-1 seroprevalence in Latin America and the Caribbean.

Population typeOutcome measuresSamplesHSV-1 seroprevalencePooled mean HSV-1 seroprevalenceHeterogeneity measures
TotalnTotalNRangeMedianMean(95% CI)Qa(p-value)I2b (%)(95% CI)Predictionc Interval (%)
Healthy general populations
Children192,0267.7–92.055.157.2 (49.7–64.6)190.8 (p<0.001)90.6 (86.8–93.3)24.7–86.7
Adults517,91738.3–98.987.684.5 (79.9–88.5)1,323.5 (p<0.001)96.2 (95.7–96.8)46.1–100
Age-mixed251670.0–71.070.570.3 (66.2–74.2) d---
All healthy general populations7210,4597.7–98.981.077.7 (72.9–82.2)2,269.1 (p<0.001)96.9 (96.5–97.3)32.6–100
Clinical populations
Adults753074.4–10091.590.9 (84.2–95.9)25.9 (p<0.001)76.8 (51.5–88.9)65.5–100
All clinical populations753074.4–10091.590.9 (84.2–95.9)25.9 (p<0.001)76.8 (51.5–88.965.5–100
Other populations
HIV positive patients252089.2–92.290.791.5 (88.8–93.7)d---
Female sex workers121,34093.1–10010098.5 (96.4–99.8)46.3 (p<0.001)76.2 (58.4–96.4)88.4–100
Men who have sex with men1170--85.3 (79.1–90.2)d---
Mixed healthy/clinical adults populations1228--96.9 (93.8–98.7)d---
Age group
≤10 years141,4387.7–76.050.549.7 (42.8–56.6)76.4 (p<0.001)83.0 (72.7–89.4)24.8–74.7
10–20 years172,29446.6–10074.677.8 (67.9–84.8)280.8 (p<0.001)94.3 (92.2–95.8)40.0–99.5
20–30 years121,92653.6–10082.582.8 (73.1–90.8)276.9 (p<0.001)96.0 (94.5–97.2)39.1–100
30–40 years91,18181.7–98.392.992.5 (89.4–95.1)24.6 (p = 0.002)67.4 (34.3–83.8)81.4–99.0
≥40 years112,12889.2–98.094.694.2 (92.7–95.5)17.5 (p = 0.064)42.9 (0.0–71.8)89.9–97.4
Mixed324,28038.3–10090.389.6 (85.7–93.9)405.7 (p<0.001)92.4 (90.2–94.0)62.9–100
Age bracket
All children192,0267.7–92.055.157.2 (49.7–64.6)190.8 (p<0.001)90.6 (86.8–93.3)24.7–86.7
All adults7310,69038.3–10091.088.4 (85.2–91.2)1,588.2 (p<0.001)95.5 (94.8–96.0)54.8–100
All age-mixed353170.0–10071.077.5 (65.8–87.5)12.3 (p = 0.002)83.7 (50.8–94.6)0.0–100
Year of publication category
<2000282,9357.7–10093.690.8 (85.8–94.9)394.7 (p<0.001)93.2 (91.2–94.7)57.1–100
2000–2009323,84429.0–10083.080.7 (73.6–87.0)847.7 (p<0.001)96.3 (95.6–97.0)34.0–100
2010–2018356,46838.3–98.078.078.8 (72.7–84.3)1,113.4 (p<0.001)96.9 (96.4–97.4)37.4–100
All studies9513,3357.7–10086.083.1 (79.3–86.5)2,772.4 (p<0.001)96.6 (96.2–97.0)40.2–100

a Q: The Cochran’s Q statistic is a measure assessing the existence of heterogeneity in pooled outcome measures, here HSV-1 seroprevalence.

b I2: A measure assessing the magnitude of between-study variation that is due to true differences in HSV-1 seroprevalence across studies rather than sampling variation.

c Prediction interval: A measure quantifying the distribution 95% interval of true HSV-1 seroprevalence around the estimated pooled mean.

d No meta-analysis was done as number of studies was <3. If there was only one study, the reported 95% CI is the 95% CI of this study. If there were two studies, both samples were merged to yield one sample size, for which the 95% CI was calculated.

Abbreviations: CI = Confidence interval, HIV = Human immunodeficiency virus, HSV-1 = Herpes simplex virus type 1.

a Study included sample size only for the total sample, but not for the strata. Each stratum sample size was set at total sample size divided by the number of strata. b The original study design of the study is prospective cohort. The included seroprevalence measures are those for the baseline measures at the onset of the study, before start of follow-up. c The original study design of the study is case-control. The included seroprevalence measures are those for each of cases and controls, separately. The population type classification was assigned based on the actual population type for each of cases and controls, separately. Abbreviations: Conv = Convenience, CS = Cross-sectional, CC = Case-control, ELISA = Enzyme-linked immunosorbent type-specific assay, FSWs = Female sex workers, HIV = Human immunodeficiency virus, HSV-1 = Herpes simplex virus type 1, IF = Indirect immunofluorescence, MAb = Monoclonal antibody, MCS = Multistage cluster sampling, NAb = Neutralizing antibody, RS = Random sampling, WB = Western blot, ZIKV = Zika virus. a Q: The Cochran’s Q statistic is a measure assessing the existence of heterogeneity in pooled outcome measures, here HSV-1 seroprevalence. b I2: A measure assessing the magnitude of between-study variation that is due to true differences in HSV-1 seroprevalence across studies rather than sampling variation. c Prediction interval: A measure quantifying the distribution 95% interval of true HSV-1 seroprevalence around the estimated pooled mean. d No meta-analysis was done as number of studies was <3. If there was only one study, the reported 95% CI is the 95% CI of this study. If there were two studies, both samples were merged to yield one sample size, for which the 95% CI was calculated. Abbreviations: CI = Confidence interval, HIV = Human immunodeficiency virus, HSV-1 = Herpes simplex virus type 1. HSV-1 seroprevalence ranged between 7.7–92.0% with a median of 55.1% among healthy children populations (n = 19), between 38.3–98.9% with a median of 87.6% among healthy adult populations (n = 51), and between 74.4–100% with a median of 91.5% among clinical adult populations (n = 7). Table 2 lists summaries for other population categories.

Pooled mean estimates for HSV-1 seroprevalence

Table 2 displays the results of the meta-analyses. The overall pooled mean HSV-1 seroprevalence (n = 95) was 83.1% (95% CI: 79.2–86.5%). The pooled mean HSV-1 seroprevalence was 57.2% (95% CI: 49.7–64.6%) among healthy children populations, 84.5% (95% CI: 79.9–88.5%) among healthy adult populations, and 90.9% (95% CI: 84.2–95.9%) among clinical adult populations. The pooled mean seroprevalence increased with age. It was lowest at 49.7% (n = 14; 95% CI: 42.8–56.6%) in those aged ≤10, followed by 77.8% (n = 17; 95% CI: 67.9–84.8%) in those aged 10–20, 82.8% (n = 12; 95% CI: 73.1–90.8%) in those aged 20–30, 92.5% (n = 9; 95% CI: 89.4–95.1%) in those aged 30–40, and 94.2% (n = 11; 95% CI: 92.7–95.5%) in those aged ≥40. The pooled mean seroprevalence decreased with time. It was highest at 90.8 (95% CI: 85.8–94.9%) before the year 2000, followed by 80.7% (95% CI: 73.6–87.0%) in 2000–2009, and 78.8% (95% CI: 72.7–84.3) in 2010–2018. Forest plots for all adult populations and all children populations can be found in S1 Fig. All meta-analyses showed evidence of heterogeneity (Table 2). Heterogeneity was attributed to true variability in seroprevalence across studies rather than chance (Table 2). The heterogeneity was affirmed by the wide prediction intervals (Table 2).

Predictors of HSV-1 seroprevalence

Table 3 and S3 Table display the results of the univariable and multivariable analyses. In the univariable analyses, age bracket, age group, sex, population type, year of publication category, year of data collection, and year of publication qualified to be included in the multivariable analysis (p<0.1). Country’s income, assay type, response rate, sample size, and sampling method all had a p-value >0.1, and hence, were not included in the multivariable analyses.
Table 3

Univariable and multivariable meta-regression models for HSV-1 seroprevalence in Latin America and the Caribbean.

Outcome measuresSamplesUnivariable analysisMultivariable analysisa
Model 1aModel 2b
Total nTotal NRR (95%CI)p-valueAdjusted R2 (%)ARR (95%CI)p-valueARR (95%CI)p-value
Population CharacteristicsAge bracketChildren192,0261.00-1.00---
Adults7310,6901.45 (1.29–1.64)<0.0011.39 (1.24–1.57)<0.001--
Age-mixed35311.35 (1.04–1.75)0.02235.371.30 (1.00–1.67)0.042--
Age group≤10141,4381.00---1.00-
10–20172,2941.44 (1.24–1.67)<0.001--1.36 (1.19–1.56)<0.001
20–30121,9261.53 (1.31–1.79)<0.001--1.44 (1.25–1.65)<0.001
30–4091,1811.76 (1.49–2.08)<0.001--1.70 (1.47–1.97)<0.001
≥40112,1281.81 (1.54–2.11)<0.001--1.81 (1.58–2.08)<0.001
Mixed324,2801.68 (1.47–1.93)<0.00153.99--1.54 (1.35–1.75)<0.001
SexFemale466,7231.00-1.00-1.00-
Male172,7710.86 (0.75–1.00)0.0530.96 (0.85–1.09)0.5720.97 (0.88–1.07)0.557
Mixed323,7510.93 (0.82–1.05)0.2773.621.03 (0.92–1.14)0.6181.00 (0.92–1.09)0.956
Population typeHealthy7210,4561.00-1.00-1.00-
Clinical75301.19 (0.99–1.43)0.0621.10 (0.93–1.29)0.2491.12 (0.97–1.28)0.116
Other162,2581.28 (1.12–1.45)<0.00117.131.15 (1.01–1.31)0.0351.16 (1.04–1.29)0.006
Country’s incomeUMIC8511,8911.00-----
HIC59251.12 (0.88–1.42)0.324----
Otherc54290.95 (0.73–1.22)0.6650.00----
Study methodology characteristicsAssay typeWestern blot273,0291.00-----
ELISA468,5080.93 (0.82–1.05)0.277----
Others221,7101.05 (0.90–1.22)0.4964.83----
Sample sized<100137911.00-----
≥1008212,4540.93 (0.75–1.08)0.3640.26----
Sampling methodNon-probability-based698,5361.00-----
Probability-based264,7010.93 (0.82–1.45)0.2101.41----
Response rate≥80225,1551.00-----
Otherwisee738,0910.91 (0.80–1.03)0.1640.93----
Temporal measuresYear of publication category<2000282,9351.00-----
2000–2009323,8440.87 (0.76–0.91)0.053----
2010–2018356,4680.86 (0.75–0.70)0.0238.67----
Year of data collection9513,3350.99 (0.99–1.00)0.0476.86----
Year of publication9513,3350.99 (0.99–0.99)0.0357.660.99 (0.99–1.00)0.3890.99 (0.99–0.99)0.043

a Variance explained by the final multivariable model 1 (adjusted R) = 42.82%.

b Variance explained by the final multivariable model 2 (adjusted R) = 69.57%.

c Other includes one measure of a low income country (Haiti) and the measures extracted from studies including different countries.

d Sample size denotes the sample size of the study population found in the original publication.

e Otherwise indicates either response rate was <80% or response rate not included in the report.

Abbreviations: ARR = Adjusted risk ratio, CI = Confidence interval, ELISA = Enzyme-linked immunosorbent type-specific assay, HIC = High-income country, HSV-1 = Herpes simplex virus type 1, RR = Risk ratio, UMIC = Upper-middle-income country.

a Variance explained by the final multivariable model 1 (adjusted R) = 42.82%. b Variance explained by the final multivariable model 2 (adjusted R) = 69.57%. c Other includes one measure of a low income country (Haiti) and the measures extracted from studies including different countries. d Sample size denotes the sample size of the study population found in the original publication. e Otherwise indicates either response rate was <80% or response rate not included in the report. Abbreviations: ARR = Adjusted risk ratio, CI = Confidence interval, ELISA = Enzyme-linked immunosorbent type-specific assay, HIC = High-income country, HSV-1 = Herpes simplex virus type 1, RR = Risk ratio, UMIC = Upper-middle-income country. Since age bracket and age group are variables that are not independent of each other, two multivariable models were analyzed, each using one of these variables. For a similar consideration, the year of publication was included in the multivariable analyses, instead of year of data collection, given its more complete data. As for the multivariable analyses including the year of publication category, instead of the linear year of publication term, the results can be found in S3 Table. The first model included age bracket, sex, population type, and year of publication. It explained 42.82% of the seroprevalence variation. In adults, seroprevalence was 1.39-fold (95% CI: 1.24–1.57) higher than that in children. The second model included age group, sex, population type, and year of publication. It explained 69.57% of the seroprevalence variation. Compared to those aged ≤10, seroprevalence was 1.36-fold (95% CI: 1.19–1.56) higher in those aged 10–20, 1.44-fold (95% CI: 1.25–1.65) higher in those aged 20–30, 1.70-fold (95% CI: 1.47–1.97) higher in those aged 30–40, and 1.81-fold (95% CI: 1.58–2.08) higher in those aged ≥40. There was evidence here for a statistically-significant declining seroprevalence over time by 0.99-fold (95% CI: 0.99–0.99) per year, in contrast to the first model analysis (Table 3) and the analyses including the year of publication as a category (S3 Table), where the evidence for the decline in sero-prevalence did not reach statistical significance.

HSV-1 virus isolation in genital ulcer disease and in genital herpes

Tables 4 and 5 summarize the extracted proportions of HSV-1 virus isolation in GUD (n = 5) and in genital herpes (n = 9), as well as their pooled mean estimates.
Table 4

Studies reporting proportions of HSV-1 virus isolation in clinically-diagnosed GUD and in clinically-diagnosed genital herpes in Latin America and the Caribbean.

Author, yearYear(s) of data collectionCountryStudy siteStudy designSampling methodPopulationHSV-1 biological assaySample sizeProportion of HSV-1 isolation (%)
HSV-1 virus isolation in clinically-diagnosed GUD (n = 5)
Gomes Naveca, 2013 [62]2008BrazilOutpatient clinicCSConvPatients with GUDPCR156.6
Gomes Naveca, 2013 [62]2008BrazilOutpatient clinicCSConvPatients with primary GUDPCR3244.0
Gomes Naveca, 2013 [62]2008BrazilOutpatient clinicCSConvPatients with recurrent GUDPCR951.1
Noda, 2016 [63]2012CubaOutpatient clinicCSConvMen with GUDPCR1130.0
Valdespino-Gomez, 1995 [64]1990MexicoCommunityCSConvFSWs with genital ulcersIFA710.0
HSV-1 virus isolation in clinically-diagnosed genital herpes (n = 9)
Balachandran, 1982 [27]-Puerto RiccoOutpatient clinicCSConvSTI clinic attendeesIFA128.3
Belli, 1990 [65]1982–83ArgentinaOutpatient clinicCSConvPatients with genital herpesIFA2520.0
Do Nascimento, 1998 [30]1995BrazilOutpatient clinicCSConvHIV patients with genital herpesPCR365.0
Hun,1987 [66]-Costa RicaOutpatient clinicCSConvSTI clinic attendeesCulture1225.0
Prabhakar, 1987 [67]1982JamaicaOutpatient clinicCSConvSTI clinic attendeesIFA400.0
Schultz, 1994 [68]1988ChileOutpatient clinicCSConvPregnant women with genital herpesDFA2010.0
Suarez, 1988 [69]1985ChileOutpatient clinicCSConvPatients with primary genital herpesIFA1428.5
Suarez, 1988 [69]1985ChileOutpatient clinicCSConvPatients with recurrent genital herpesIFA619.8
Suarez, 1989 [70]1984ChileOutpatient clinicCSConvWomen with genital herpesDFA1323.1

Abbreviations: Conv = Convenience, CS = Cross sectional, DFA = Direct fluorescent assay, FSWs = Female sex workers, GUD = Genital ulcer disease, HSV-1 = Herpes simplex virus type 1, IFA = Indirect immunofluorescence assay, PCR = Polymerase chain reaction, RS = Random Sampling, STI = Sexually transmitted infection.

Table 5

Pooled proportions of HSV-1 virus isolation in clinically-diagnosed GUD and in clinically-diagnosed genital herpes in Latin America and the Caribbean.

Population typeOutcome measuresSamplesProportion of HSV-1 isolation (%)Pooled proportion of HSV-1 isolation (%)Heterogeneity measures
TotalnTotalNRangeMedianMean(95% CI)Qa(p-value)I2b (%)(95% CI)Prediction Intervalc (%)
Patients with clinically-diagnosed GUD56180.0–6.61.10.9 (0.0–3.6)12.9 (p = 0.0116)69.1 (20.7–88.0)0.0–14.6
Patients with clinically-diagnosed genital herpes92330.0–28.510.010.9 (4.4–19.4)21.1 (p = 0.0069)62.1 (21.7–81.6)0.0–40.4

a Q: The Cochran’s Q statistic is a measure assessing the existence of heterogeneity in pooled outcome measures, here proportions of HSV-1 virus isolation.

b I2: A measure assessing the magnitude of between-study variation that is due to true differences in proportions of HSV-1 virus isolation across studies rather than sampling variation.

c Prediction interval: A measure quantifying the distribution 95% interval of true proportions of HSV-1 virus isolation around the estimated pooled mean.

Abbreviations: CI = Confidence interval, GUD = Genital ulcer disease, HSV-1 = Herpes simplex virus type 1.

Abbreviations: Conv = Convenience, CS = Cross sectional, DFA = Direct fluorescent assay, FSWs = Female sex workers, GUD = Genital ulcer disease, HSV-1 = Herpes simplex virus type 1, IFA = Indirect immunofluorescence assay, PCR = Polymerase chain reaction, RS = Random Sampling, STI = Sexually transmitted infection. a Q: The Cochran’s Q statistic is a measure assessing the existence of heterogeneity in pooled outcome measures, here proportions of HSV-1 virus isolation. b I2: A measure assessing the magnitude of between-study variation that is due to true differences in proportions of HSV-1 virus isolation across studies rather than sampling variation. c Prediction interval: A measure quantifying the distribution 95% interval of true proportions of HSV-1 virus isolation around the estimated pooled mean. Abbreviations: CI = Confidence interval, GUD = Genital ulcer disease, HSV-1 = Herpes simplex virus type 1. In GUD cases, the virus isolation proportion ranged between 0.0–6.6%, with a median of 1.1% and a pooled mean of 0.9% (95% CI: 0.0–3.6%). In genital herpes cases, the proportion ranged between 0.0–28.5%, with a median of 10.0% and a pooled mean of 10.9% (95% CI: 4.4–19.4%). Both meta-analyses of proportions showed strong evidence of heterogeneity (Table 5). Forest plots can be found in S2 Fig. A total of 31 reports were included in the systematic review, while an additional 12 reports were excluded due to potential issues in their diagnostic method (Fig 2). Summary of the precision and ROB assessments are in S4 Table. High precision was found in the majority of studies (62.9%). High ROB in the sampling method domain was found in the vast majority of studies (94.3%). Low ROB in the response rate domain was found in 25.7% of studies, while the remaining studies had a high ROB (2.9%), or an unclear ROB (71.4%). Since none of the study characteristics of sample size, sampling method, and response rate were found associated with HSV-1 seroprevalence (Table 3), it is not likely that precision nor ROB have affected the results of the present study.

Discussion

The systematic review and meta-analytics reported here indicate that HSV-1 infection is widely prevalent in Latin America and the Caribbean, at a seroprevalence level that is higher than that of the global population at 67% [1]. Nearly 60% of children and 90% of adults are infected, a higher seroprevalence than that in Western Countries [31] and Asia [8], though lower than that in Africa [32] and the Middle East and North Africa (MENA) [33]. Seroprevalence increased steadily with age, but most HSV-1 acquisitions still occurred in childhood (Tables 2 and 3). Age was by far the strongest predictor of infection, explaining alone >50% of the seroprevalence variation (Table 3). Meanwhile, sex, clinical condition, and country’s income did not affect HSV-1 seroprevalence (Table 3), in broad agreement with the results of similar studies for Africa [32], Asia [8], and MENA [33]. These findings affirm the notion that HSV-1 is a truly general population infection, with largely homogenous exposure risk in the population. There was evidence for a declining seroprevalence over the last three decades, but the exact effect size of the decline and nature of the decline (linear or not) are not yet certain with currently available data (Tables 2 and 3 and S3 Table). While seroprevalence declines have been also observed in North America and Europe [31, 34–41], no evidence for such declines was found in Africa [32], Asia [8], and MENA [33]. The large gap in HSV-1 seroprevalence between children and adults (Tables 2 and 3), supports also the interpretation of recent declines in seroprevalence, with the currently older cohorts experiencing higher infection risk in earlier times. As observed in North America [31], improvements in hygiene and standard of living may have driven the seroprevalence declines. With this evidence for a possible slow transition in HSV-1 epidemiology in Latin America and the Caribbean, there is a cause for concern for genital herpes, as increasingly a larger fraction of adolescents may initiate sexual activity with no antibodies to protect them against acquiring HSV-1 sexually, and thus at risk of genital herpes. Indeed, we found evidence supporting a role for HSV-1 as the etiological cause of genital herpes (Tables 4 and 5), though at rates much lower than those observed in Western countries [4, 5, 7, 9–11] and Asia [8]. This study has limitations. Data were available only for 14 mostly populous countries (Tables 1 and 4), with no data found for the remaining 32 smaller countries. Studies varied in methods and quality and used different diagnostic assays, with potentially different sensitivity and specificity profiles [16, 17]. However, no effect was found on seroprevalence for assay type, sample size, sampling method, and response rate (Table 3), indicating that the variability in study methods may not have impacted the results and findings of the present study.

Conclusions

As in North America, Europe, and Asia [5, 7–11, 31, 35, 42], there is evidence for a possible transitioning HSV-1 epidemiology in Latin America and the Caribbean, though at a slower rate and with still limited contribution for HSV-1 in genital herpes and as a sexually transmitted infection. HSV-1 seroprevalence appears to be declining, with the younger cohorts experiencing lower infection risk than those experienced by the younger cohorts in earlier times. Yet, HSV-1 persists as a widely prevalent infection in this region, with 60% of children and 90% of adults being infected. These findings support the need for surveillance to monitor trends in seroprevalence and genital herpes etiology, and highlight the need for a vaccine to prevent infection and associated disease burden.

Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist.

(DOCX) Click here for additional data file.

Data sources and search criteria for systematically reviewing HSV-1 epidemiology in Latin America and the Caribbean.

(DOCX) Click here for additional data file.

Multivariable meta-regression models for HSV-1 seroprevalence in Latin America and the Caribbean including the categorical stratification by year of publication.

(DOCX) Click here for additional data file.

Summary of the precision assessment and risk of bias (ROB) assessment for the studies reporting HSV-1 seroprevalence in Latin America and the Caribbean.

(DOCX) Click here for additional data file.

List of the 46 countries included in our definition for the Latin America and the Caribbean region.

(DOCX) Click here for additional data file.

List of variables extracted from the relevant reports meeting the inclusion criteria.

(DOCX) Click here for additional data file.

Forest plots presenting the outcomes of the pooled mean HSV-1 seroprevalence among children and adult populations in Latin America and the Caribbean.

(DOCX) Click here for additional data file.

Forest plots presenting the outcomes of the pooled mean proportions of HSV-1 virus isolation in clinically-diagnosed genital ulcer disease and in clinically-diagnosed genital herpes in Latin America and the Caribbean.

(DOCX) Click here for additional data file.
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