Predicting adverse pregnancy outcome in Rwanda using machine learning techniques.

Background: Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contributing to morbidity, mortality, and long-term developmental challenges. This study aimed to predict these outcomes in Rwanda using supervised machine learning algorithms.

Methods: This cross-sectional study utilized data from the Rwanda Demographic and Health Survey (RDHS, 2019-2020) involving 14,634 women.

Estimation of the Population Size of Street- and Venue-Based Female Sex Workers and Sexually Exploited Minors in Rwanda in 2022: 3-Source Capture-Recapture.

Background: HIV surveillance among key populations is a priority in all epidemic settings. Female sex workers (FSWs) globally as well as in Rwanda are disproportionately affected by the HIV epidemic; hence, the Rwanda HIV and AIDS National Strategic Plan (2018-2024) has adopted regular surveillance of population size estimation (PSE) of FSWs every 2-3 years.

Objective: We aimed at estimating, for the fourth time, the population size of street- and venue-based FSWs and sexually exploited minors aged ≥15 years in Rwanda.

Population Size Estimation of Men Who Have Sex With Men in Rwanda: Three-Source Capture-Recapture Method.

Background: Globally, men who have sex with men (MSM) continue to bear a disproportionately high burden of HIV infection. Rwanda experiences a mixed HIV epidemic, which is generalized in the adult population, with aspects of a concentrated epidemic among certain key populations at higher risk of HIV infection, including MSM. Limited data exist to estimate the population size of MSM at a national scale; hence, an important piece is missing in determining the denominators to use in estimates for policy makers, program managers, and planners to effectively monitor HIV epidemic control.

Prediction of Stunting Among Under-5 Children in Rwanda Using Machine Learning Techniques.

Objectives: Rwanda reported a stunting rate of 33% in 2020, decreasing from 38% in 2015; however, stunting remains an issue. Globally, child deaths from malnutrition stand at 45%. The best options for the early detection and treatment of stunting should be made a community policy priority, and health services remain an issue.

Inter-Pregnancy Intervals and Maternal Morbidity: New Evidence from Rwanda.

The effects of short and long pregnancy intervals on maternal morbidity have hardly been investigated. This research analyses these effects using logistic regression in two steps. First, data from the Rwanda Demographic and Health Survey 2010 are used to study delivery referrals to District hospitals.

The Effects of Interpregnancy Intervals and Previous Pregnancy Outcome on Fetal Loss in Rwanda (1996-2010).

In 2005, a WHO consultation meeting on pregnancy intervals recommended a minimum interval of 6 months after a pregnancy disruption and an interval of two years after a live birth before attempting another pregnancy. Since then, studies have found contradictory evidence on the effect of shorter intervals after a pregnancy disruption. A binary regression analysis on 21532 last pregnancy outcomes from the 2000, 2005, and 2010 Rwanda Demographic and Health Surveys was done to assess the combined effects of the preceding pregnancy outcome and the interpregnancy intervals (IPIs) on fetal mortality in Rwanda.

THE EFFECT OF PREGNANCY SPACING ON FETAL SURVIVAL AND NEONATAL MORTALITY IN RWANDA: A HECKMAN SELECTION ANALYSIS.

Most studies on birth intervals and infant mortality ignore pregnancies that do not result in live births. Yet, fetal deaths are important in infant mortality analyses for three reasons: ignoring fetal deaths between two live births lengthens the measured interval between births, implying that short intervals are underestimated; the recommended inter-pregnancy interval (IPI) after a fetal loss is shorter (6 months) than after a live birth (24 months), as the effect of IPI on outcomes might differ according to the previous type of pregnancy outcome; fetal death will selectively reduce the population at risk of neonatal mortality, leading to biased results. This study uses the Heckman selection model to simultaneously estimate the combined effect of IPI duration and the type of pregnancy outcome at the start of the interval on pregnancy survival and neonatal mortality.