BackgroundDespite the availability of individual-level data of infants accessing HIV DNA-PCR testing service, there has been little in-depth analysis of such data. Therefore, we describe trends in ...risk of HIV infection among Malawi’s HIV-exposed infants (HEI) with DNA-PCR HIV test result from 2013 to 2020.MethodsThis is an implementation study using routinely collected patient-level HIV DNA-PCR test result data extracted from the national Laboratory Management Information System database managed by the Department of HIV/AIDS between 1 January 2013 and 30 June 2020. We calculated frequencies, proportions and odds ratio (OR) with their associated 95% CI. We performed a random-effects logistic regression to determine the risk factors associated with HIV infection in infants, controlling for the spatial autocorrelation between districts and adjusting for other variables.ResultsWe evaluated 255 229 HEI across 750 facilities in 28 districts. The HIV DNA-PCR test was performed within 2 months in 57% of the children. The overall HIV prevalence among all tested HEI between 2013 and 2020 was 7.2% (95% CI 7.1% to 7.3%). We observed a decreasing trend in the proportion of HEI that tested HIV positive from 7.0% (95% CI 6.6% to 7.4%) in 2013 to 5.7% (95% CI 5.4% to 5.9%) in 2015 followed by an increase to 9.9% (95% CI 9.6% to 10.2%) in 2017 and thereafter a decreasing trend between 2017 (i.e. 9.72% (95%CI: 9.43-10.01)) and 2020 (i.e. 3.86% (95%CI: 3.34-4.37)). The HIV prevalence increased by age of the HEI. There was spatial heterogeneity of HIV prevalence between districts of Malawi. The prevalence of HIV was higher among the HEI from the Northern region of Malawi.ConclusionThe main findings of the study are that the DNA test is performed within 2 months only in 57% of the children, that the decreasing trend of HIV prevalence among HEI observed up to 2015 was followed by an increase up to 2017 and a decrease afterwards, and that the risk of HIV infection increased with age at HIV testing. We summarised spatial and temporal trends of risk of HIV infection among HEI in Malawi between 2013 and 2020. There is need to ensure that all the HEI are enrolled in HIV care by 8 weeks of age in order to further reduce the risk of HIV in this population.
Measures introduced to reduce the spread of SARS-CoV-2 by the Malawi government and the national HIV care program might have compromised treatment outcomes of patients living with HIV on ...antiretroviral therapy (ART). We studied viral load (VL) outcomes before and during the COVID-19 epidemic in Malawi.
In this population-based cohort study, we included all routine VL measurements collected from July 2019 to December 2020 in about 650 ART clinics in Malawi. We examined differences between pandemic periods (before/during COVID-19) for i) VL monitoring, and ii) VL suppression (VLS: <1,000 copies/ml). For i) we studied the number of VL measurements over time and assessed predictors of missed measurements before and during COVID-19 in logistic regression models. For ii) we estimated the odds of VLS before and during the COVID-19 epidemic stratified by treatment regimen using generalized estimation equations adjusted for age, sex, time on ART, and type of biological sample. We imputed missing treatment regimens by population-calibrated multiple imputation.
We included 607,894 routine VL samples from 556,281 patients. VL testing declined during COVID-19 (243,729; 40%) compared to before COVID-19 (365,265; 60%), but predictors of missing tests were similar in the two periods. VLS rates increased slightly from 93% before to 94% during COVID-19. Compared to before COVID-19, the odds of VLS increased during COVID-19 for patients on protease inhibitor-based (PI) regimens (adjusted odds ratio aOR 1.22, 95% CI: 0.99-1.49) and for patients on integrase strand transfer inhibitor-based (INSTI) regimens (aOR 1.10, 95% CI: 1.03-1.17). There was no difference in VLS between the two periods among patients on nonnucleoside reverse transcriptase inhibitor-based (NNRTI) regimens. VLS varied by age, sex, regimen, and duration on ART, ranging from 45.1% (95% CI 40.3-50.0%) to 97.2% (95% CI 96.9-97.4%).
There was a significant decline in VL monitoring during COVID-19, but we did not find clear evidence that the pandemic reduced VL suppression rates. Routine scheduled VL monitoring, targeted adherence support, and timely regimen switches for patients with treatment failure remain critical to improving VLS.
Objective
To describe the prevalence of HIV viral suppression and assess the factors associated with HIV viral suppression among persons receiving antiretroviral therapy (ART) in Malawi in 2021.
...Methods
Implementation study using routinely collected patient‐level HIV RNA‐PCR test result data extracted from the national Laboratory Management Information System (LIMS) database managed by the Department of HIV/AIDS in 2021. We calculated frequencies, proportions and odds ratios (OR) of HIV viral suppression with their associated 95% confidence intervals (95%CIs). We performed a random‐effects logistic regression to determine the risk factors associated with HIV viral suppression among ART patients, controlling for the spatial autocorrelation between districts and adjusting for other variables.
Results
We evaluated 515,797 adults and children receiving ART and having a viral load test in 2021. Of these, 92.8% had HIV viral suppression. ART patients living in urban areas had lower likelihood of HIV viral suppression than those living in rural areas (adjusted OR aOR = 0.95, 95%CI: 0.92–0.99, p = 0.01). There was an increasing trend in HIV viral suppression with increasing ART duration. Routine VL monitoring samples were 39% more likely to have suppressed VL values than confirmatory HIV VL monitoring samples (aOR = 1.39; 95%CI: 1.34–1.43, p < 0.001).
Conclusion
This is the first national analysis of Malawi HIV VL data from LIMS. Our findings show the need to particularly consider the urban residents, those below 20 years, males, those on ART for less than a year as well as those on specific ARV regimens in order to persistently suppress HIV VL and consequently achieve the goal of achieving HIV VL suppression by 2030.
In settings without etiologic testing for sexually transmitted infections (STIs), programs rely on STI symptom data to inform priorities. To evaluate whether self-reported STI symptoms in household ...surveys consistently represent the STI burden, we compared symptomatic infection rates between survey self-reporting and health facility case reporting in Malawi.
We analyzed self-reported symptoms and treatment seeking in the past year among sexually active adults from 4 Malawi Demographic and Health Surveys between 2000 and 2015. Bayesian mixed-effects models were used to estimate temporal trends, spatial variation, and sociodemographic determinants. Survey reporting was compared with health facility syndromic diagnoses between 2014 and 2021.
In surveys, 11.0% (95% confidence interval, 10.7%-11.4%) of adults reported STI or STI-related symptoms in the last year, of whom 54.2% (52.8%-55.7%) sought treatment. In facilities, the mean annual symptomatic case diagnosis rate was 3.3%. Survey-reported treatment in the last year was 3.8% (95% credible interval, 2.3%-6.1%) for genital ulcer, 3.8% (2.0%-6.7%) for vaginal discharge, and 2.6% (1.2%-4.7%) for urethral discharge. Mean annual diagnosis rates at facilities were 0.5% for genital ulcer, 2.2% for vaginal discharge, and 2.0% for urethral discharge. Both data sources indicated a higher burden of symptoms among women, individuals older than 25 years, and those in Southern Malawi.
Survey and facility case reports indicated similar spatial and demographic patterns of STI symptom burden and care seeking, but implied large differences in the magnitude and relative burden of symptoms, particularly genital ulcer, which could affect program priorities. Targeted etiologic surveillance would improve interpretation of these data to enable more comprehensive STI surveillance.
Introduction
HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or ...equivalent subnational administrative level. We developed a Bayesian small‐area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five‐year age groups.
Methods
Small‐area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district‐level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016–2018.
Results
Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty‐eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city.
Conclusions
The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.
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