Success or failure of critical steps in community case management of malaria with rapid diagnostic tests: a systematic review

Background: Malaria still causes high morbidity and mortality around the world, mainly in sub-Saharan Africa. Community case management of malaria (CCMm) by community health workers (CHWs) is one of the strategies to combat the disease by increasing access to malaria treatment. Currently, the World Health Organization recommends to treat only confirmed malaria cases, rather than to give presumptive treatment. Objectives. This systematic review aims to provide a comprehensive overview of the success or failure of critical steps in CCMm with rapid diagnostic tests (RDTs). Methods. The databases of Medline, Embase, the Cochrane Library, the library of the \u27Malaria in Pregnancy\u27 consortium, and Web of Science were used to find studies on CCMm with RDTs in SSA. Studies were selected according to inclusion and exclusion criteria, subsequently risk of bias was assessed and data extracted. Results: 27 articles were included. CHWs were able to correctly perform RDTs, although specificity levels were variable. CHWs showed high adherence to test results, but in some studies a substantial group of RDT negatives received treatment. High risk of bias was found for morbidity and mortality studies, therefore, effects on morbidity and mortality could not be estimated. Uptake and acceptance by the community was high, however negative-tested patients did not always follow up referral advice. Drug or RDT stock-outs and limited information on CHW motivation are bottlenecks for sustainable implementation. RDT-based CCMm was found to be cost effective for the correct treatment of malaria in areas with low to medium malaria prevalence, but study designs were not optimal. Discussion. Trained CHWs can deliver high quality care for malaria using RDTs. However, lower RDT specificity could lead to missed diagnoses of non-malarial causes of fever. Other threats for CCMm are non-adherence to negative test results and low referral completion. Integrated CCM may solve some of these issues. Unfortunately, morbidity and mortality are not adequately investigated. More information is needed about influencing sociocultural aspects, CHW motivation and stock supply. Conclusion: CCMm is generally well executed by CHWs, but there are several barriers for its success. Integrated CCM may overcome some of these barriers

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Sampling distribution for a class of estimators for nonregular linear processes

Let {Xt; T = 1, 2,...} be a linear process with a location parameter [theta] defined by Xt - [theta] = [Sigma]0[infinity]grZt-r where {Zt; T = 0, ±1,...} is a sequence of independent and identically distributed random variables, with E[short parallel]Z1[short parallel][delta] 0. If [delta] [greater-or-equal, slanted] 1 we assume further than E(Z1) = 0. Let [eta] = [delta] if 0nonregular linear process location parameter linear estimator symmetric stable distribution

Bahadur-Kiefer representations for GM-estimators in linear Markov models with errors in variables

We consider a class of generalized M(GM)-estimators for the autoregressive parameter in a linear Markov model with errors in variables. We show, under some minimal regularity assumptions, that these estimators have almost sure representations of the Bahadur-Kiefer type and consequently they are consistent and asymptotically normal.Errors in variables Linear Markov scheme Almost sure convergence Bahadur-Kiefer type

Asymptotic estimate of probability of misclassification for discriminant rules based on density estimates

Let X1,..., X1 and Y1,..., Yn be independent random samples from the distribution functions (d.f.) F and G respectively. Assume that F' = f and G' = g. The discriminant rule for classifying and independently sampled observation Z to F if and to G, otherwise where l and n are the estimates of f and g respectively based on a common kernel function and the training X- and Y-samples, are considered optimal in some sense. Let Pf denote the probability measure under the assumption that Z ~ F and set P0 = Pf(f(Z) > g(Z)) and . In this article we have derived the rate at which PN --> P0 as N = l + n --> [infinity], for the situation where l = n, F(x) = TM(x - [theta]2) and G(x) = M(x - [theta]1) for some symmetric d.f. M and parameters [theta]1, [theta]2. We have examined a few special cases of M and have established that the rate of convergence of PN to P0 depends critically on the tail behavior of m = M'.optimal classification rule probability of misclassification kernel function density estimates

Sampling Properties of U-statistics for a Class of Stationary Nonlinear Processes

Stationary nonlinear processes, U-statistics, Large sample properties,