ABSTRACT
We analyse household resilience capacities during the COVID-19 pandemic in the fishing communities along Lake Malawi by using FAO's resilience index measurement assessment (RIMA) methodology. The study is based on a sample of 400 households, and we employ the multiple indicators multiple causes (MIMIC) model to estimate resilience capacities. The model uses household food security indicators as development outcomes. Our findings show that the COVID-19 pandemic significantly reduces household food security and resilience capacity. COVID-19 shocks that significantly reduce household resilience capacities are death and illness of a household member. Important pillars for resilience building are assets, access to basic services and adaptive capacity. These findings point to the need to build assets of the households, build their adaptive capacity, and identify innovative ways of improving access to basic services to build household resilience capacities in the fishing communities. We recommend providing external support to households that have been directly affected by the pandemic through the death or illness of a member because their capacities to bounce back on their own significantly declines.
ABSTRACT
The increase in health research in sub-Saharan Africa (SSA) has generated large amounts of data and led to a high demand for biostatisticians to analyse these data locally and quickly. Donor-funded initiatives exist to address the dearth in statistical capacity, but few initiatives have been led by African institutions. The Sub-Saharan African Consortium for Advanced Biostatistics (SSACAB) aims to improve biostatistical capacity in Africa according to the needs identified by African institutions, through (collaborative) masters and doctoral training in biostatistics. We describe the SSACAB Consortium, which comprises 11 universities and four research institutions- supported by four European universities. SSACAB builds on existing resources to strengthen biostatistics for health research with a focus on supporting biostatisticians to become research leaders; building a critical mass of biostatisticians, and networking institutions and biostatisticians across SSA. In 2015 only four institutions had established Masters programmes in biostatistics and SSACAB supported the remaining institutions to develop Masters programmes. In 2019 the University of the Witwatersrand became the first African institution to gain Royal Statistical Society accreditation for a Biostatistics MSc programme. A total of 150 fellows have been awarded scholarships to date of which 123 are Masters fellowships (41 female) of which with 58 have already graduated. Graduates have been employed in African academic (19) and research (15) institutions and 10 have enrolled for PhD studies. A total of 27 (10 female) PhD fellowships have been awarded; 4 of them are due to graduate by 2020. To date, SSACAB Masters and PhD students have published 17 and 31 peer-reviewed articles, respectively. SSACAB has also facilitated well-attended conferences, face-to-face and online short courses. Pooling the limited biostatistics resources in SSA, and combining with co-funding from external partners is an effective strategy for the development and teaching of advanced biostatistics methods, supervision and mentoring of PhD candidates.
ABSTRACT
BACKGROUND: Malaria is a major public health problem in Malawi, however, quantifying its burden in a population is a challenge. Routine hospital data provide a proxy for measuring the incidence of severe malaria and for crudely estimating morbidity rates. Using such data, this paper proposes a method to describe trends, patterns and factors associated with in-hospital mortality attributed to the disease. METHODS: We develop semiparametric regression models which allow joint analysis of nonlinear effects of calendar time and continuous covariates, spatially structured variation, unstructured heterogeneity, and other fixed covariates. Modelling and inference use the fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulation techniques. The methodology is applied to analyse data arising from paediatric wards in Zomba district, Malawi, between 2002 and 2003. RESULTS AND CONCLUSION: We observe that the risk of dying in hospital is lower in the dry season, and for children who travel a distance of less than 5 kms to the hospital, but increases for those who are referred to the hospital. The results also indicate significant differences in both structured and unstructured spatial effects, and the health facility effects reveal considerable differences by type of facility or practice. More importantly, our approach shows non-linearities in the effect of metrical covariates on the probability of dying in hospital. The study emphasizes that the methodological framework used provides a useful tool for analysing the data at hand and of similar structure.
