Prereferral rectal artesunate and referral completion among children with suspected severe malaria in the Democratic Republic of the Congo, Nigeria and Uganda.

INTRODUCTION: Children who receive prereferral rectal artesunate (RAS) require urgent referral to a health facility where appropriate treatment for severe malaria can be provided. However, the rapid improvement of a child's condition after RAS administration may influence a caregiver's decision to follow this recommendation. Currently, the evidence on the effect of RAS on referral completion is limited. METHODS: An observational study accompanied the roll-out of RAS in three malaria endemic settings in the Democratic Republic of the Congo (DRC), Nigeria and Uganda. Community health workers and primary health centres enrolled children under 5 years with suspected severe malaria before and after the roll-out of RAS. All children were followed up 28 days after enrolment to assess their treatment-seeking pathways. RESULTS: Referral completion was 67% (1408/2104) in DRC, 48% (287/600) in Nigeria and 58% (2170/3745) in Uganda. In DRC and Uganda, RAS users were less likely to complete referral than RAS non-users in the pre-roll-out phase (adjusted OR (aOR)=0.48, 95% CI 0.30 to 0.77 and aOR=0.72, 95% CI 0.58 to 0.88, respectively). Among children seeking care from a primary health centre in Nigeria, RAS users were less likely to complete referral compared with RAS non-users in the post-roll-out phase (aOR=0.18, 95% CI 0.05 to 0.71). In Uganda, among children who completed referral, RAS users were significantly more likely to complete referral on time than RAS non-users enrolled in the pre-roll-out phase (aOR=1.81, 95% CI 1.17 to 2.79). CONCLUSIONS: The findings of this study raise legitimate concerns that the roll-out of RAS may lead to lower referral completion in children who were administered prereferral RAS. To ensure that community-based programmes are effectively implemented, barriers to referral completion need to be addressed at all levels. Alternative effective treatment options should be provided to children unable to complete referral. TRIAL REGISTRSTION NUMBER: NCT03568344; ClinicalTrials.gov.

Modeling Nigerian Covid-19 cases: A comparative analysis of models and estimators.

COVID-19 remains a major pandemic currently threatening all the countries of the world. In Nigeria, there were 1, 932 COVID-19 confirmed cases, 319 discharged cases and 58 deaths as of 30th April 2020. This paper, therefore, subjected the daily cumulative reported COVID-19 cases of these three variables to nine (9) curve estimation statistical models in simple, quadratic, cubic, and quartic forms. It further identified the best of the thirty-six (36) models and used the same for prediction and forecasting purposes. The data collected by the Nigeria Centre for Disease Control for sixty-four (64) days, two (2) months and three (3), were daily monitored and eventually analyzed. We identified the best models to be Quartic Linear Regression Model with an autocorrelated error of order 1 (AR(1)); and found the Ordinary Least Squares, Cochrane Orcutt, Hildreth-Lu, and Prais-Winsten and Least Absolute Deviation (LAD) estimators useful to estimate the models' parameters. Consequently, we recommended the daily cumulative forecast values of the LAD estimator for May and June 2020 with a 99% confidence level. The forecast values are alarming, and so, the Nigerian Government needs to hastily review her activities and interventions towards COVID-19 to provide some tactical and robust structures and measures to avert these challenges.