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Background: Brazil is among the countries in South America where the COVID-19 pandemic has hit the general population hardest. Self-testing for SARS-CoV-2 infection is one of the community-based strategies that could help asymptomatic individuals at-risk of COVID-19, as well as those living in areas that are difficult for health personnel to reach, to know their infectious status and contribute to impeding further transmission of the virus., Methods: A population-based survey was conducted in November 2021, to assess the acceptability of rapid SARS-CoV-2 antigen self-testing among the population of São Paulo. Survey respondents were approached at more than 400 different street-points that were randomly selected using a five-stage randomization process. A 35-item structured questionnaire was used. Dependent variables for our analyses were the likelihood to use and willingness to pay for self-testing, and the likelihood of taking preventive measures to prevent onward transmission of SARS-CoV-2 following a reactive self-test result. Bivariate and multivariate regression analyses were performed., Results: Overall, 417 respondents (44.12% female) participated; 19.66% had previously had COVID-19 disease. A minority (9.59%) felt at high-risk of COVID-19. The majority of both females and males (73.91% and 60.09%, respectively) were in favor of the idea of SARS-CoV-2 self-testing. Overall, if self-tests were available, almost half of the sample would be very likely (n = 54, 12.95%) or likely (n = 151, 36.21%) to use one if they felt they needed to. Upon receiving a positive self-test result, the majority of respondents would communicate it (88.49%), request facility-based post-test counseling (98.32%), self-isolate (97.60%), and warn their close contacts (96.64%)., Conclusion: Rapid SARS-CoV-2 antigen self-testing could be an acceptable screening tool in São Paulo. The population would be empowered by having access to a technology that would allow them to test, even if asymptomatic, when traveling, or going to work or school. If there is a surge in the incidence of cases, self-testing could be a good approach for mass case detection by Brazil's already overstretched Unified Health System., (© 2022. The Author(s).)

Background: Antimicrobial resistance (AMR) is one of the greatest global health challenges today, but burden assessment is hindered by uncertainty of AMR prevalence estimates. Geographical representation of AMR estimates typically pools data collected from several laboratories; however, these aggregations may introduce bias by not accounting for the heterogeneity of the population that each laboratory represents., Methods: We used AMR data from up to 381 laboratories in the United States from The Surveillance Network to evaluate methods for estimating uncertainty of AMR prevalence estimates. We constructed confidence intervals for the proportion of resistant isolates using (1) methods that account for the clustered structure of the data, and (2) standard methods that assume data independence. Using samples of the full dataset with increasing facility coverage levels, we examined how likely the estimated confidence intervals were to include the population mean., Results: Methods constructing 95% confidence intervals while accounting for possible within-cluster correlations (Survey and standard methods adjusted to employ cluster-robust errors), were more likely to include the sample mean than standard methods (Logit, Wilson score and Jeffreys interval) operating under the assumption of independence. While increased geographical coverage improved the probability of encompassing the mean for all methods, large samples still did not compensate for the bias introduced from the violation of the data independence assumption., Conclusion: General methods for estimating the confidence intervals of AMR rates that assume data are independent, are likely to produce biased results. When feasible, the clustered structure of the data and any possible intra-cluster variation should be accounted for when calculating confidence intervals around AMR estimates, in order to better capture the uncertainty of prevalence estimates.

Objectives/purpose: The costs attributable to antimicrobial resistance (AMR) remain theoretical and largely unspecified. Current figures fail to capture the full health and economic burden caused by AMR across human, animal, and environmental health; historically many studies have considered only direct costs associated with human infection from a hospital perspective, primarily from high-income countries. The Global Antimicrobial Resistance Platform for ONE-Burden Estimates (GAP-ON€) network has developed a framework to help guide AMR costing exercises in any part of the world as a first step towards more comprehensive analyses for comparing AMR interventions at the local level as well as more harmonized analyses for quantifying the full economic burden attributable to AMR at the global level., Methods: GAP-ON€ (funded under the JPIAMR 8th call (Virtual Research Institute) is composed of 19 international networks and institutions active in the field of AMR. For this project, the Network operated by means of Delphi rounds, teleconferences and face-to-face meetings. The resulting costing framework takes a bottom-up approach to incorporate all relevant costs imposed by an AMR bacterial microbe in a patient, in an animal, or in the environment up through to the societal level., Results: The framework itemizes the epidemiological data as well as the direct and indirect cost components needed to build a realistic cost picture for AMR. While the framework lists a large number of relevant pathogens for which this framework could be used to explore the costs, the framework is sufficiently generic to facilitate the costing of other resistant pathogens, including those of other aetiologies., Conclusion: In order to conduct cost-effectiveness analyses to choose amongst different AMR-related interventions at local level, the costing of AMR should be done according to local epidemiological priorities and local health service norms. Yet the use of a common framework across settings allows for the results of such studies to contribute to cumulative estimates that can serve as the basis of broader policy decisions at the international level such as how to steer R&D funding and how to prioritize AMR amongst other issues. Indeed, it is only by building a realistic cost picture that we can make informed decisions on how best to tackle major health threats.

Background: Available data on antibiotic resistance in sub-Saharan Africa is limited despite its increasing threat to global public health. As there is no previous study on antibiotic resistance in patients with clinical features of healthcare-associated infections (HAIs) in Sierra Leone, research is needed to inform public health policies. Our study aimed to assess antibiotic resistance rates from isolates in the urine and sputum samples of patients with clinical features of HAIs., Methodology: We conducted a cross-sectional study of adult inpatients aged ≥18 years at Connaught Hospital, an urban tertiary care hospital in Freetown between February and June 2018., Results: Over the course of the study, we enrolled 164 patients. Risk factors for HAIs were previous antibiotic use (93.3%), comorbidities (58.5%) and age (≥65 years) (23.9%). Of the 164 samples, 89.6% were urine. Bacterial growth was recorded in 58.8% of cultured specimens; the type of specimen was an independent predictor of bacterial growth (p < 0.021). The most common isolates were Escherichia coli and Klebsiella pneumoniae; 29.2% and 19.0% in urine samples and 18.8% and 31.3% in sputum samples, respectively. The overall resistance rates were 58% for all extended-spectrum beta-lactamase (ESBL)-producing organisms, 13.4% for carbapenem-resistant non-lactose fermenting gram-negative bacilli, 8.7% for carbapenem-resistant Acinetobacter baumannii (CRAB) and 1.3% for carbapenem-resistant Enterobacteriaceae (CRE). There were no carbapenem-resistant P. aeruginosa (CRPA) isolates but all Staphylococcus aureus isolates were methicillin-resistant S. aureus., Conclusion: We demonstrated a high prevalence rate of ESBL-producing organisms which are a significant burden at the main tertiary hospital in Sierra Leone. Urgent action is needed to strengthen microbiological diagnostic infrastructure, initiate surveillance on antibiotic resistance and develop and implement policy framework on antibiotic stewardship.

Background: Against the backdrop of renewed efforts to control tuberculosis (TB) worldwide, there is a need for improved methods to estimate the public health impact of TB programmes. Such methods should not only address the improved outcomes amongst those receiving care but should also account for the impact of TB services on reducing transmission., Methods: Vital registration data in India are not sufficiently reliable for estimates of TB mortality. As an alternative approach, we developed a mathematical model of TB transmission dynamics and mortality, capturing the scale-up of DOTS in India, through the rollout of the Revised National TB Control Programme (RNTCP). We used available data from the literature to calculate TB mortality hazards amongst untreated TB; amongst cases treated under RNTCP; and amongst cases treated under non-RNTCP conditions. Using a Bayesian evidence synthesis framework, we combined these data with current estimates for the TB burden in India to calibrate the transmission model. We simulated the national TB epidemic in the presence and absence of the DOTS programme, measuring lives saved as the difference in TB deaths between these scenarios., Results: From 1997 to 2016, India's RNTCP has saved 7.75 million lives (95% Bayesian credible interval 6.29-8.82 million). We estimate that 42% of this impact was due to the 'indirect' effects of the RNTCP in averting transmission as well as improving treatment outcomes., Conclusions: When expanding high-quality TB services, a substantial proportion of overall impact derives from preventive, as well as curative, benefits. Mathematical models, together with sufficient data, can be a helpful tool in estimating the true population impact of major disease control programmes.

Background: Schizophrenia remains a priority condition in mental health policy and service development because of its early onset, severity and consequences for affected individuals and households., Aims and Methods: This paper reports on an 'extended' cost-effectiveness analysis (ECEA) for schizophrenia treatment in India, which seeks to evaluate through a modeling approach not only the costs and health effects of intervention but also the consequences of a policy of universal public finance (UPF) on health and financial outcomes across income quintiles., Results: Using plausible values for input parameters, we conclude that health gains from UPF are concentrated among the poorest, whereas the non-health gains in the form of out-of-pocket private expenditures averted due to UPF are concentrated among the richest income quintiles. Value of insurance is the highest for the poorest quintile and declines with income., Conclusions: Universal public finance can play a crucial role in ameliorating the adverse economic and social consequences of schizophrenia and its treatment in resource-constrained settings where health insurance coverage is generally poor. This paper shows the potential distributional and financial risk protection effects of treating schizophrenia.

Background: Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized., Methods: The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts., Results and Discussion: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both)., Discussion: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location., Conclusions: The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales.