Status of the HIV epidemic in Manicaland, east Zimbabwe prior to the outbreak of the COVID-19 pandemic

Abstract

Background: Manicaland province in eastern Zimbabwe has a high incidence of HIV. Completion of the seventh round of the Manicaland Survey in 2018-2019 provided the opportunity to assess the state of the epidemic prior to the start of the COVID-19 pandemic. The study aims were to: a) estimate HIV seroprevalence and assess whether prevalence has declined since the last round of the survey (2012-2013), b) describe and analyse the socio-demographic and behavioural risk factors for HIV infection and c) describe the HIV treatment cascade.

Methods: Participants were administered individual questionnaires collecting data on socio-demographic characteristics, sexual relationships, HIV prevention methods and treatment access, and were tested for HIV. Descriptive analyses were followed by univariate and multivariate analyses of risk factors for HIV seropositvity using logistic regression modelling based on the proximate-determinants framework.

Results: HIV prevalence was 11.3% [95% CI; 10.6-12.0] and was higher in females than males up to 45-49 years. Since 2012-2013 HIV prevalence has significantly declined in 30-44 year-olds in males, and 20-44 year-olds in females. The HIV epidemic has aged since 2012-2013, with an increase in the mean age of HIV positive persons from 38 to 41 years. Socio-demographic determinants of HIV prevalence were church denomination in males, site-type, wealth-status, employment sector and alcohol use in females, and age and marital status in both sexes. Behavioural determinants associated with increased odds of HIV were a higher number of regular sexual partners (lifetime), non-regular sexual partners (lifetime) and condom use in both sexes, and early sexual debut and concomitant STIs in females; medical circumcision was protective in males. HIV status awareness among participants testing positive in our study was low at 66.2%. ART coverage amongst all participants testing positive for HIV in our study was 65.0% and was lower in urban areas than rural areas, particularly in males.

Conclusions: Prevalence has declined, and ART coverage increased, since 2012-2013. Majority of the associations with prevalence hypothesised by the theoretical framework were not observed in our data, likely due to underreporting of sexual risk behaviours or the treatment-as-prevention effect of ART curtailing the probability of transmission despite high levels of sexual risk behaviour. Further reductions in HIV incidence require strengthened primary prevention, HIV testing and linkage to risk behaviour counselling services. Our results serve as a valuable baseline against which to measure the impact of the COVID-19 pandemic on HIV prevalence and its determinants in Manicaland, Zimbabwe, and target interventions appropriately.

Fig 1. Proximate and underlying determinants of HIV infection.

Socio-demographic characteristics influence HIV infection status via proximate factors (sexual risk behaviours) which in turn modify the biological risk of HIV infection. For instance, the number of sexual partners, non-regular partners, concurrent partners, transactional sex and age of sexual debut influence the probability of exposure of susceptible to infected individuals, while condom use, concomitant STIs and medical circumcision affect the efficiency of transmission per sexual contact. * Alcohol use is considered as a background factor as it is believed that its impact on HIV infection is mediated by sexual risk behaviours.

Fig 2. Breakdown of weighted HIV seroprevalence across socio-demographic characteristics.

Error bars represent 95% CI.

Fig 3. Comparison of HIV prevalence between 2012–2013 and 2018–2019 in overlapping age-groups and study sites.

Error bars represent 95% CI. Asterisks (*) indicate differences that are statistically significant at the level of p<0.05.

Fig 4. Breakdown of ART coverage by site-type and sex.

ART coverage is shown among participants who tested positive in our study, regardless of HIV status awareness or previous diagnosis. Error bars represent 95% CI. Asterisks (*) indicate differences that are statistically significant at the level of p<0.05.