COVID-19 self-testing: Countries accelerating policies ahead of WHO guidelines during pandemics, a global consultation.

The widespread use of antigen-detection rapid diagnostic tests (Ag-RDTs) has revolutionized SARS-CoV-2 (COVID-19) testing, particularly through the option of self-testing. The full extent of Ag-RDT utilization for self-testing, however, remains largely unexplored. To inform the development of WHO guidance on COVID-19 self-testing, we conducted a global consultation to gather the views and experiences of policy makers, researchers, and implementers worldwide. The consultation was conducted by disseminating a WHO questionnaire through professional networks via email and social media, encouraging onward sharing. We used a cross-sectional design with both closed and open-ended questions related to policy and program information concerning the regulation, availability, target population, indications, implementation, benefits, and challenges of COVID-19 self-testing (C19ST). We defined self-testing as tests performed and interpreted by an untrained individual, often at home. Descriptive summaries, cross-tabulations, and proportions were used to calculate outcomes at the global level and by WHO region and World Bank income classifications. All information was collated and reported according to WHO guideline development standards and practice for global consultations. Between 01 and 11 February 2022, 844 individuals from 139 countries responded to the survey, with 45% reporting affiliation with governments and 47% operating at the national level. 504 respondents from 101 countries reported policies supporting C19ST for a range of use cases, including symptomatic and asymptomatic populations. More respondents from low-and-middle-income countries (LMICs) than high-income countries (HICs) reported a lack of an C19ST policy (61 vs 11 countries) and low population-level reach of C19ST. Respondents with C19ST experience perceived that the tests were mostly acceptable to target populations, provided significant benefits, and highlighted several key challenges to be addressed for increased success. Reported costs varied widely, ranging from specific programmes enabling free access to certain users and others with high costs via the private sector. Based on this consultation, systems for the regulatory review, policy development and implementation of C19ST appeared to be much more common in HIC when compared to LIC in early 2022, though most respondents indicated self-testing was available to some extent (101 out of 139 countries) in their country. Addressing such global inequities is critical for ensuring access to innovative and impactful interventions in the context of a public health emergency of international concern. The challenges and opportunities highlighted by key stakeholders could be valuable to consider as future testing strategies are being set for outbreak-prone diseases.

A pragmatic health centre-based evaluation comparing the effectiveness of a PCV13 schedule change from 3+0 to 2+1 in a high pneumococcal carriage and disease burden setting in Malawi: a study protocol.

INTRODUCTION: Streptococcus pneumoniae (the pneumococcus) is commonly carried as a commensal bacterium in the nasopharynx but can cause life-threatening disease. Transmission occurs by human respiratory droplets and interruption of this process provides herd immunity. A 2017 WHO Consultation on Optimisation of pneumococcal conjugate vaccines (PCV) Impact highlighted a substantial research gap in investigating why the impact of PCV vaccines in low-income countries has been lower than expected. Malawi introduced the 13-valent PCV (PCV13) into the national Expanded Programme of Immunisations in 2011, using a 3+0 (3 primary +0 booster doses) schedule. With evidence of greater impact of a 2+1 (2 primary +1 booster dose) schedule in other settings, including South Africa, Malawi's National Immunisations Technical Advisory Group is seeking evidence of adequate superiority of a 2+1 schedule to inform vaccine policy. METHODS: A pragmatic health centre-based evaluation comparing impact of a PCV13 schedule change from 3+0 to 2+1 in Blantyre district, Malawi. Twenty government health centres will be randomly selected, with ten implementing a 2+1 and 10 to continue with the 3+0 schedule. Health centres implementing 3+0 will serve as the direct comparator in evaluating 2+1 providing superior direct and indirect protection against pneumococcal carriage. Pneumococcal carriage surveys will evaluate carriage prevalence among children 15-24 months, randomised at household level, and schoolgoers 5-10 years of age, randomly selected from school registers. Carriage surveys will be conducted 18 and 33 months following 2+1 implementation. ANALYSIS: The primary endpoint is powered to detect an effect size of 50% reduction in vaccine serotype (VT) carriage among vaccinated children 15-24 months old, expecting a 14% and 7% VT carriage prevalence in the 3+0 and 2+1 arms, respectively. ETHICS AND DISSEMINATION: The study has been approved by the Malawi College of Medicine Research Ethics Committee (COMREC; Ref: P05.19.2680), the University College London Research Ethics Committee (Ref: 8603.002) and the University of Liverpool Research Ethics Committee (Ref: 5439). The results from this study will be actively disseminated through manuscript publications and conference presentations. TRIAL REGISTRATION NUMBER: NCT04078997.

Using structured additive regression models to estimate risk factors of malaria: analysis of 2010 Malawi malaria indicator survey data.

BACKGROUND: After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. METHODS: We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. RESULTS: Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. CONCLUSIONS: The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.

Relative importance of climatic, geographic and socio-economic determinants of malaria in Malawi.

BACKGROUND: Malaria transmission is influenced by variations in meteorological conditions, which impact the biology of the parasite and its vector, but also socio-economic conditions, such as levels of urbanization, poverty and education, which impact human vulnerability and vector habitat. The many potential drivers of malaria, both extrinsic, such as climate, and intrinsic, such as population immunity are often difficult to disentangle. This presents a challenge for the modelling of malaria risk in space and time. METHODS: A statistical mixed model framework is proposed to model malaria risk at the district level in Malawi, using an age-stratified spatio-temporal dataset of malaria cases from July 2004 to June 2011. Several climatic, geographic and socio-economic factors thought to influence malaria incidence were tested in an exploratory model. In order to account for the unobserved confounding factors that influence malaria, which are not accounted for using measured covariates, a generalized linear mixed model was adopted, which included structured and unstructured spatial and temporal random effects. A hierarchical Bayesian framework using Markov chain Monte Carlo simulation was used for model fitting and prediction. RESULTS: Using a stepwise model selection procedure, several explanatory variables were identified to have significant associations with malaria including climatic, cartographic and socio-economic data. Once intervention variations, unobserved confounding factors and spatial correlation were considered in a Bayesian framework, a final model emerged with statistically significant predictor variables limited to average precipitation (quadratic relation) and average temperature during the three months previous to the month of interest. CONCLUSIONS: When modelling malaria risk in Malawi it is important to account for spatial and temporal heterogeneity and correlation between districts. Once observed and unobserved confounding factors are allowed for, precipitation and temperature in the months prior to the malaria season of interest are found to significantly determine spatial and temporal variations of malaria incidence. Climate information was found to improve the estimation of malaria relative risk in 41% of the districts in Malawi, particularly at higher altitudes where transmission is irregular. This highlights the potential value of climate-driven seasonal malaria forecasts.