Modeling time to death for under-five children in Malawi using 2015/16 Demographic and Health Survey: a survival analysis.

BACKGROUND: Malawi has one of the highest under-five mortality rates in Sub Sahara Africa. Understanding the factors that contribute to child mortality in Malawi is crucial for the development and implementation of effective interventions to reduce child mortality. The aim of this study is to use survival analysis in modeling time to death for under-five children in Malawi. In turn, identify potential risk factors for child mortality and inform the development of interventions to reduce child mortality in the country. METHOD: This study used data from all births that occurred in the five years leading up to the 2015/16 Malawi Demographic and Health Survey. The Frailty hazard model was applied to predict infant survival in Malawi. In this analysis, the outcome of interest was death and it had two possible outcomes: "dead" or "alive". Age at death was regarded as the survival time variable. Infants who were still alive at the time of the study as of the day of the interview were considered as censored observations in the analysis. RESULTS: A total of 17,286 live births born during the 5 years preceding the survey were analysed. The study found that the risk of death was higher among children born to mothers aged 30-39 and 40 or older compared to teen mothers. Infants whose mothers attended fewer than four antenatal care visits were also found to be at a higher risk of death. On the other hand, the study found that using mosquito nets and early breastfeeding were associated with a lower risk of death, as were being male and coming from a wealthier household. CONCLUSION: The study reveals a notable decline in infant mortality rates as under-five children age, underscoring the challenge of ensuring newborn survival. Factors such as maternal age, birth order, socioeconomic status, mosquito net usage, early breastfeeding initiation, geographic location, and child's sex are key predictors of under-five mortality. To address this, public health strategies should prioritize interventions targeting these predictors to reduce under-five mortality rates.

Profit inefficiency of goat farming in Malawi: A Bayesian approach.

Goat farms located in villages constitute an important sub-sector to buffer household livelihoods against climate shocks in absence of insurance markets, and thus the need to intensify production to meet the growing goat meat demand. There has been little attempt to quantify the efficiency of goat farms and the associated drivers. Potential initiatives to bolster goat farm incomes have not gone beyond production. Using the Bayesian Stochastic Frontier Approach and Malawi's national Integrated Household Panel Survey data from 2010 to 2019, we analyze the profit efficiency of goat farming and the priority drivers that influence inefficiencies across production plants. The findings reveal that farmers are operating below the profit frontier and 71% of the profit-loss is influenced by farm characteristics. The results further suggest that policies involving stirring commercializing and specialization are key to closing the efficiency gap. Finally, the study proposes new policy directions, namely, government provision of livestock extension services to farmers, incorporating goat farming into women's empowerment programs, and provision of access to tailor-made livestock microfinance loans.