ABSTRACT
BACKGROUND: Routine health system data are central to monitoring HIV trends. In Mozambique, the reported number of women receiving antenatal care (ANC) and antiretroviral therapy for prevention of mother-to-child transmission (PMTCT) has exceeded the Spectrum-estimated number of pregnant women since 2017. In some provinces, reported HIV prevalence in pregnant women has declined faster than epidemiologically plausible. We hypothesized that these issues are linked and caused by programmatic overenumeration of HIV-negative pregnant women at ANC. METHODS: We triangulated program-reported ANC client numbers with survey-based fertility estimates and facility birth data adjusted for the proportion of facility births. We used survey-reported ANC attendance to produce adjusted time series of HIV prevalence in pregnant women, adjusted for hypothesized program double counting. We calibrated the Spectrum HIV estimation models to adjusted HIV prevalence data to produce adjusted adult and pediatric HIV estimates. RESULTS: ANC client numbers were not consistent with facility birth data or modeled population estimates indicating ANC data quality issues in all provinces. Adjusted provincial ANC HIV prevalence in 2021 was median 45% [interquartile range 35%-52% or 2.3 percentage points (interquartile range 2.5-3.5)] higher than reported HIV prevalence. In 2021, calibrating to adjusted antenatal HIV prevalence lowered PMTCT coverage to less than 100% in most provinces and increased the modeled number of new child infections by 35%. The adjusted results better reconciled adult and pediatric antiretroviral treatment coverage and antenatal HIV prevalence with regional fertility estimates. CONCLUSIONS: Adjusting HIV prevalence in pregnant women using nationally representative household survey data on ANC attendance produced estimates more consistent with surveillance data. The number of children living with HIV in Mozambique has been substantially underestimated because of biased routine ANC prevalence. Renewed focus on HIV surveillance among pregnant women would improve PMTCT coverage and pediatric HIV estimates.
Subject(s)
HIV Infections , Pregnancy , Adult , Female , Humans , Child , Mozambique/epidemiology , Prevalence , HIV Infections/epidemiology , Infectious Disease Transmission, Vertical/prevention & control , Research DesignABSTRACT
BACKGROUND: Cost-effectiveness analysis (CEA) is a standard tool for evaluating health programs and informing decisions about resource allocation and prioritization. Most CEAs evaluating health interventions in low- and middle-income countries adopt a health sector perspective, accounting for resources funded by international donors and country governments, while often excluding out-of-pocket expenditures and time costs borne by program beneficiaries. Even when patients' costs are included, a companion analysis focused on the patient perspective is rarely performed. We view this as a missed opportunity. METHODS: We developed methods for assessing intervention affordability and evaluating whether optimal interventions from the health sector perspective also represent efficient and affordable options for patients. We mapped the five different patterns that a comparison of the perspective results can yield into a practical framework, and we provided guidance for researchers and decision-makers on how to use results from multiple perspectives. To illustrate the methodology, we conducted a CEA of six HIV treatment delivery models in Mozambique. We conducted a Monte Carlo microsimulation with probabilistic sensitivity analysis from both patient and health sector perspectives, generating incremental cost-effectiveness ratios for the treatment approaches. We also calculated annualized patient costs for the treatment approaches, comparing the costs with an affordability threshold. We then compared the cost-effectiveness and affordability results from the two perspectives using the framework we developed. RESULTS: In this case, the two perspectives did not produce a shared optimal approach for HIV treatment at the willingness-to-pay threshold of 0.3 × Mozambique's annual GDP per capita per DALY averted. However, the clinical 6-month antiretroviral drug distribution strategy, which is optimal from the health sector perspective, is efficient and affordable from the patient perspective. All treatment approaches, except clinical 1-month distributions of antiretroviral drugs which were standard before Covid-19, had an annual cost to patients less than the country's annual average for out-of-pocket health expenditures. CONCLUSION: Including a patient perspective in CEAs and explicitly considering affordability offers decision-makers additional insights either by confirming that the optimal strategy from the health sector perspective is also efficient and affordable from the patient perspective or by identifying incongruencies in value or affordability that could affect patient participation.
ABSTRACT
Objectivo: Mapear o potencial risco de transmissão do novo coronavírus em Moçambique de modo a identificar os distritos cujas características sociodemográficas favorecem a propagação do vírus. Métodos: Usou-se a modelação espacial para determinar o risco relativo de propagação da COVID-19 num distrito em relação ao outro com base nos seguintes factores sociodemográficos: densidade populacional, tamanho médio de agregado familiar, percentagem da população jovem de 15-34 anos e percentagem da população que vive num raio de 2 km de uma estrada classificada. Primeiro, para cada factor foi estimado um risco relativo dividindo os distritos em quintis, e, em segundo lugar, os riscos individuais de cada factor foram somados com igual peso para estimar o risco agregado de transmissão da COVID-19 por distrito. Resultados: Dezanove distritos localizados sobretudo nos principais centros urbanos e no corredor da Beira apresentam alto risco de propagação da COVID-19 em função das suas características sociodemográficas; 24 distritos mostram risco médio-alto e distribuem-se pelas regiões centro e sul do país; 60 distritos localizados nas regiões centro e sul e no interior da região norte apresentam risco médio e; 58 distritos mostram risco médio-baixo ou baixo de transmissão da COVID-19 e encontram-se no litoral centro-norte do país. Conclusão: Os distritos cujo perfil sociodemográfico é favorável à rápida propagação do novo coronavírus são os das grandes cidades e os localizados nas principais rotas de transporte. No entanto, este padrão de risco é susceptível de alterações em função da celeridade, abrangência e níveis de observância das medidas de prevenção e/ou de mitigação da COVID-19. Assim, recomenda-se que as medidas de prevenção e mitigação tenham em conta o risco potencial em cada distrito em função das suas características sociodemográficas.
Objective: To map the potential risk of COVID-19 transmission in Mozambique in order to identify districts with sociodemographic characteristics that favour the spread of coronavirus. Methods: Spatial modelling was used to determine the relative risk of COVID-19 transmission in a certain district in relation to other districts based on the following sociodemographic factors: population density, mean number of household members, the percentage of the young population aged 15-34 and the proportion of a district's population living within two kilometres of a classified road. First, a relative risk due to each factor was estimated grouping the districts into quintiles and, second, the individual risks were added with equal weight to estimate the aggregate relative risk of COVID-19 transmission per district. Results: Nineteen districts located in the main urban centres and along the Beira corridor were found to be at a high relative risk of COVID-19 transmission; 24 districts located mainly in central and southern regions display a medium-high risk category; 60 districts located in the central and southern regions and in the hinterland of the northern region show a medium risk category and; 58 districts exhibit a medium-low or low risk category of COVID-19 transmission and are mainly located at the eastern part of the central-north region. Conclusion: The districts with sociodemographic profile favouring the spread of the new coronavirus are those in the big cities and those located along the main transportation routes. However, the pattern of risk is subject to changes due to the speed, coverage and level of compliance with COVID-19 prevention and mitigation measures. It is recommended that COVID-19 prevention and mitigation measures should take into account the potential risk of each district.
