Investigating the upsurge of malaria prevalence in Zambia between 2010 and 2015: a decomposition of determinants.

BACKGROUND: Malaria is among the top causes of mortality and morbidity in Zambia. Efforts to control, prevent, and eliminate it have been intensified in the past two decades which has contributed to reductions in malaria prevalence and under-five mortality. However, there was a 21% upsurge in malaria prevalence between 2010 and 2015. Zambia is one of the only 13 countries to record an increase in malaria among 91 countries monitored by the World Health Organization in 2015. This study investigated the upsurge by decomposition of drivers of malaria. METHODS: The study used secondary data from three waves of nationally representative cross-sectional surveys on key malaria indicators conducted in 2010, 2012 and 2015. Using multivariable logistic regression, determinants of malaria prevalence were identified and then marginal effects of each determinant were derived. The marginal effects were then combined with changes in coverage rates of determinants between 2010 and 2015 to obtain the magnitude of how much each variable contributed to the change in the malaria prevalence. RESULTS: The odds ratio of malaria for those who slept under an insecticide-treated net (ITN) was 0.90 (95% CI 0.77-0.97), indoor residual spraying (IRS) was 0.66 (95% CI 0.49-0.89), urban residence was 0.23 (95% CI 0.15-0.37), standard house was 0.40 (95% CI 0.35-0.71) and age group 12-59 Months against those below 12 months was 4.04 (95% CI 2.80-5.81). Decomposition of prevalence changes by determinants showed that IRS reduced malaria prevalence by - 0.3% and ITNs by - 0.2% however, these reductions were overridden by increases in prevalence due to increases in the proportion of more at-risk children aged 12-59 months by + 2.3% and rural residents by + 2.2%. CONCLUSION: The increases in interventions, such as ITNs and IRS, were shown to have contributed to malaria reduction in 2015; however, changes in demographics such as increases in the proportion of more at risk groups among under-five children and rural residents may have overridden the impact of these interventions and resulted in an overall increase. The upsurge in malaria in 2015 compared to 2010 may not have been due to weaknesses in programme interventions but due to increases in more at-risk children and rural residents compared to 2010. The apparent increase in rural residents in the sample population may not have been a true reflection of the population structure but due to oversampling in rural areas which was not fully adjusted for. The increase in malaria prevalence may therefore have been overestimated.

Experiences of Early and Enhanced Clinical Exposure for Postgraduate Neonatal Nursing Students at the University of Zambia, School of Nursing Sciences: Lessons and Implications for the Future.

Background and Objectives: Early and Enhanced Clinical Exposure immediately places postgraduate students in a clinical setting and incorporates continual hands-on instruction throughout their studies. It aims to motivate students by strengthening their academics, improving clinical and communication skills, and increasing their confidence. The underlying principles are to provide a clinical context and to ensure that the patient remains the centre of learning. The School of Nursing Sciences implemented this model in 2021 to produce hands-on Masters-level neonatal practitioners who can work in multidisciplinary clinical contexts. Therefore, this study explored the experiences of postgraduate nursing students on the Early and Enhanced Clinical Exposure model and draw implications for the future. Methods: A phenomenological study design was utilized at the University of Zambia, School of Nursing Sciences and comprised of eight Master of Science Neonatal Nursing students in their second year. Convenience sampling was used to select the study site and participants. Data was collected between 15th January 2023 and 31st January 2023 using an in-depth interview guide. Audio recording and notes were transcribed immediately after data collection. Data analysis was conducted using thematic analysis and codes and themes were constructed from the coded data. Ethical clearance and permission were sought before conducting the study. Results: Four major themes emerged from the study: identity and role confusion, challenging and hectic experiences, positive educational experiences, and personal and professional growth. These themes contributed to the promotion of evidence-based practice by helping students to assess, diagnose, and treat various conditions, as well as gain interest, experience, knowledge, and exposure. Conclusion: The model has a significant impact on motivation to learn, as evidenced by reported increased skill level with potential for use in clinical practice. It is recommended that it be implemented in all postgraduate programs for full-time students.

Modelling malaria reduction in a highly endemic country: Evidence from household survey, climate, and program data in Zambia.

Substantial efforts have seen the reduction in malaria prevalence from 33% in 2006 to 19.4% in 2015 in Zambia. Many studies have used effect measures, such as odds ratios, of malaria interventions without combining this information with coverage levels of the interventions to assess how malaria prevalence would change if these interventions were scaled up. We contribute to filling this gap by combining intervention coverage information with marginal predictions to model the extent to which key interventions can bring down malaria in Zambia. We used logistic regression models and derived marginal effects using repeated cross-sectional survey data from the Malaria Indicator Survey (MIS) datasets for Zambia collected in 2010, 2012 and 2015. Average monthly temperature and rainfall data were obtained from climate explorer a satellite-generated database. We then conducted a counterfactual analysis using the estimated marginal effects and various hypothetical levels of intervention coverage to assess how different levels of coverage would affect malaria prevalence. Increasing IRS and ITNs from the 2015 levels of coverage of 28.9% and 58.9% respectively to at least 80% and rising standard housing to 20% from the 13.4% in 2015 may bring malaria prevalence down to below 15%. If the percentage of modern houses were increased further to 90%, malaria prevalence might decrease to 10%. Other than ITN and IRS, streamlining and increasing of the percentage of standard houses in malaria fight would augment and bring malaria down to the levels needed for focal malaria elimination. The effects of ITNs, IRS and Standard housing were pronounced in high than low epidemiological areas.