Area-specific covid-19 effects on health services utilization in the Democratic Republic of the Congo using routine health information system data.

BACKGROUND: Since March 2020, the COVID-19 pandemic has shocked health systems worldwide. This analysis investigated the effects of the pandemic on basic health services utilization in the Democratic Republic of the Congo (DRC) and examined the variability of COVID effects in the capital city Kinshasa, in other urban areas, and in rural areas. METHODS: We estimated time trends models using national health information system data to replicate pre-COVID-19 (i.e., January 2017-February 2020) trajectories of health service utilization, and then used those models to estimate what the levels would have been in the absence of COVID-19 during the pandemic period, starting in March 2020 through March 2021. We classified the difference between the observed and predicted levels as the effect of COVID-19 on health services. We estimated 95% confidence intervals and p-values to examine if the effect of the pandemic, nationally and within specific geographies, was statistically significant. RESULTS: Our results indicate that COVID-19 negatively impacted health services and subsequent recovery varied by service type and by geographical area. COVID-19 had a lasting impact on overall service utilization as well as on malaria and pneumonia-related visits among young children in the DRC. We also found that the effects of COVID-19 were even more immediate and stronger in the capital city of Kinshasa compared with the national effect. Both nationally and in Kinshasa, most affected services had slow and incomplete recovery to expected levels. Therefore, our analysis indicates that COVID-19 continued to affect health services in the DRC throughout the first year of the pandemic. CONCLUSIONS: The methodology used in this article allows for examining the variability in magnitude, timing, and duration of the COVID effects within geographical areas of the DRC and nationally. This analytical procedure based on national health information system data could be applied to surveil health service disruptions and better inform rapid responses from health service managers and policymakers.

A practical approach for geographic prioritization and targeting of insecticide-treated net distribution campaigns during public health emergencies and in resource-limited settings.

BACKGROUND: The use of data in targeting malaria control efforts is essential for optimal use of resources. This work provides a practical mechanism for prioritizing geographic areas for insecticide-treated net (ITN) distribution campaigns in settings with limited resources. METHODS: A GIS-based weighted approach was adopted to categorize and rank administrative units based on data that can be applied in various country contexts where Plasmodium falciparum transmission is reported. Malaria intervention and risk factors were used to rank local government areas (LGAs) in Nigeria for prioritization during mass ITN distribution campaigns. Each factor was assigned a unique weight that was obtained through application of the analytic hierarchy process (AHP). The weight was then multiplied by a value based on natural groupings inherent in the data, or the presence or absence of a given intervention. Risk scores for each factor were then summated to generate a composite unique risk score for each LGA. This risk score was translated into a prioritization map which ranks each LGA from low to high priority in terms of timing of ITN distributions. RESULTS: A case study using data from Nigeria showed that a major component that influenced the prioritization scheme was ITN access. Sensitivity analysis results indicate that changes to the methodology used to quantify ITN access did not modify outputs substantially. Some 120 LGAs were categorized as 'extremely high' or 'high' priority when a spatially interpolated ITN access layer was used. When prioritization scores were calculated using DHS-reported state level ITN access, 108 (90.0%) of the 120 LGAs were also categorized as being extremely high or high priority. The geospatial heterogeneity found among input risk factors suggests that a range of variables and covariates should be considered when using data to inform ITN distributions. CONCLUSION: The authors provide a tool for prioritizing regions in terms of timing of ITN distributions. It serves as a base upon which a wider range of vector control interventions could be targeted. Its value added can be found in its potential for application in multiple country contexts, expediated timeframe for producing outputs, and its use of systematically collected malaria indicators in informing prioritization.

Projecting the Impact of the COVID-19 Pandemic on Child Marriage.

PURPOSE: The study projects the potential impact of COVID-19 on child marriage in the five countries in which the burden of child marriage is the largest: Bangladesh, Brazil, Ethiopia, India, and Nigeria. METHODS: The projected impact of the pandemic on child marriage is based on a Markov model. A review of empirical and theoretical literature informed construction and parameter estimates of five pathways through which we expect an elevated marriage hazard: death of a parent, interruption of education, pregnancy risk, household income shocks, and reduced access to programs and services. Models are produced for an unmitigated scenario and a mitigated scenario in which effective interventions are applied to reduce the impact. RESULTS: The total number of excess child marriages in these five countries could range from 3.5 million to 4.9 million in the unmitigated scenario and from 1.8 million to 2.7 million in the mitigated scenario. The elevated risk compared with the baseline projection would continue until 2035. CONCLUSIONS: These projections represent the impact in five countries that account for 50% of child marriages globally, implying that if similar patterns hold, we might expect the number of excess child marriages due to the pandemic to reach 7 million to 10 million globally. These estimates are necessarily subject to high levels of uncertainty because of limited evidence on the impacts in relation to child marriage and for parameter estimates. It will likely take years to understand the full impact of the pandemic. Despite these limitations, the potential for harm is unquestionably large.