Differences between persons with and without disability in HIV prevalence, testing, treatment, and care cascade in Tanzania: a cross-sectional study using population-based data.

BACKGROUND: Persons with disability may have a higher HIV prevalence and be less likely than persons without disability to know their HIV-positive status, access antiretroviral therapy (ART), and suppress their HIV viral load (HIV care cascade). However, studies examining differences between persons with and without disability in HIV prevalence and the HIV care cascade are lacking. Using the Tanzania HIV Impact Survey (THIS) data collected between October 2016 and August 2017, we assessed differences in HIV prevalence and progress towards achieving the 2020 HIV care cascade target between persons with and without disability. METHODS: Using the Washington Group Short Set (WG-SS) Questions on Disability, we defined disability as having a functional difficulty in any of the six life domains (seeing, hearing, walking/climbing, remembering/ concentrating, self-care, and communicating). We classified respondents as disabled if they responded having either "Some Difficulty", "A lot of difficulties" or "Unable to" in any of the WG-SS Questions. We presented the sample characteristics by disability status and analyzed the achievement of the cascade target by disability status, and sex. We used multivariable logistic regressions, and adjusted for age, sex, rural-urban residence, education, and wealth quintile. RESULTS: A total of 31,579 respondents aged 15 years and older had HIV test results. Of these 1,831 tested HIV-positive, corresponding to an estimated HIV prevalence of 4.9% (CI: 4.5 - 5.2%) among the adult population in Tanzania. The median age of respondents who tested HIV-positive was 32 years (with IQR of 21-45 years). HIV prevalence was higher (5.7%, 95% CI: 5.3-7.4%) among persons with disability than persons without disability (4.3%, 95% CI: 4.0 - 4.6%). Before adjustment, compared to women without disability, more women with disability were aware of their HIV-positive status (n = 101, 79.0%, 95% CI: 68.0-87.0% versus n = 703, 63.0%, 95% CI: 59.1-66.7%) and accessed ART more frequently (n = 98, 98.7%, 95% CI: 95.3-99.7% versus n = 661, 94.7%, 95% CI: 92.6-96.3%). After adjusting for socio-demographic characteristics, the odds of having HIV and of accessing ART did not differ between persons with and without disability. However, PLHIV with disability had higher odds of being aware of their HIV-positive status (aOR 1.69, 95% 1.05-2.71) than PLHIV without disability. Men living with HIV and with disability had lower odds (aOR = 0.23, 95% CI: 0.06-0.86) to suppress HIV viral loads than their counterparts without disability. CONCLUSION: We found no significant differences in the odds of having HIV and of accessing ART between persons with and without disability in Tanzania. While PLHIV and disability, were often aware of their HIV-positive status than their non-disabled counterparts, men living with HIV and with disability may have been disadvantaged in having suppressed HIV viral loads. These differences are correctable with disability-inclusive HIV programming. HIV surveys around the world should include questions on disability to measure potential differences in HIV prevalence and in attaining the 2025 HIV care cascade target between persons with and without disability.

An Automated Literature Review Tool (LiteRev) for Streamlining and Accelerating Research Using Natural Language Processing and Machine Learning: Descriptive Performance Evaluation Study.

BACKGROUND: Literature reviews (LRs) identify, evaluate, and synthesize relevant papers to a particular research question to advance understanding and support decision-making. However, LRs, especially traditional systematic reviews, are slow, resource-intensive, and become outdated quickly. OBJECTIVE: LiteRev is an advanced and enhanced version of an existing automation tool designed to assist researchers in conducting LRs through the implementation of cutting-edge technologies such as natural language processing and machine learning techniques. In this paper, we present a comprehensive explanation of LiteRev's capabilities, its methodology, and an evaluation of its accuracy and efficiency to a manual LR, highlighting the benefits of using LiteRev. METHODS: Based on the user's query, LiteRev performs an automated search on a wide range of open-access databases and retrieves relevant metadata on the resulting papers, including abstracts or full texts when available. These abstracts (or full texts) are text processed and represented as a term frequency-inverse document frequency matrix. Using dimensionality reduction (pairwise controlled manifold approximation) and clustering (hierarchical density-based spatial clustering of applications with noise) techniques, the corpus is divided into different topics described by a list of the most important keywords. The user can then select one or several topics of interest, enter additional keywords to refine its search, or provide key papers to the research question. Based on these inputs, LiteRev performs a k-nearest neighbor (k-NN) search and suggests a list of potentially interesting papers. By tagging the relevant ones, the user triggers new k-NN searches until no additional paper is suggested for screening. To assess the performance of LiteRev, we ran it in parallel to a manual LR on the burden and care for acute and early HIV infection in sub-Saharan Africa. We assessed the performance of LiteRev using true and false predictive values, recall, and work saved over sampling. RESULTS: LiteRev extracted, processed, and transformed text into a term frequency-inverse document frequency matrix of 631 unique papers from PubMed. The topic modeling module identified 16 topics and highlighted 2 topics of interest to the research question. Based on 18 key papers, the k-NNs module suggested 193 papers for screening out of 613 papers in total (31.5% of the whole corpus) and correctly identified 64 relevant papers out of the 87 papers found by the manual abstract screening (recall rate of 73.6%). Compared to the manual full text screening, LiteRev identified 42 relevant papers out of the 48 papers found manually (recall rate of 87.5%). This represents a total work saved over sampling of 56%. CONCLUSIONS: We presented the features and functionalities of LiteRev, an automation tool that uses natural language processing and machine learning methods to streamline and accelerate LRs and support researchers in getting quick and in-depth overviews on any topic of interest.

A Platform for Data-Centric, Continuous Epidemiological Analyses (EpiGraphHub): Descriptive Analysis.

BACKGROUND: Guaranteeing durability, provenance, accessibility, and trust in open data sets can be challenging for researchers and organizations that rely on public repositories of data critical for epidemiology and other health analytics. The required data repositories are often difficult to locate and may require conversion to a standard data format. Data-hosting websites may also change or become unavailable without warning. A single change to the rules in one repository can hinder updating a public dashboard reliant on data pulled from external sources. These concerns are particularly challenging at the international level, because policies on systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs. OBJECTIVE: In this paper, we introduce a comprehensive public health data platform, EpiGraphHub, that aims to provide a single interoperable repository for open health and related data. METHODS: The platform, curated by the international research community, allows secure local integration of sensitive data while facilitating the development of data-driven applications and reports for decision-makers. Its main components include centrally managed databases with fine-grained access control to data, fully automated and documented data collection and transformation, and a powerful web-based data exploration and visualization tool. RESULTS: EpiGraphHub is already being used for hosting a growing collection of open data sets and for automating epidemiological analyses based on them. The project has also released an open-source software library with the analytical methods used in the platform. CONCLUSIONS: The platform is fully open source and open to external users. It is in active development with the goal of maximizing its value for large-scale public health studies.

Clinical and programmatic outcomes of HIV-exposed infants enrolled in care at geographically diverse clinics, 1997-2021: A cohort study.

BACKGROUND: Although 1·3 million women with HIV give birth annually, care and outcomes for HIV-exposed infants remain incompletely understood. We analyzed programmatic and health indicators in a large, multidecade global dataset of linked mother-infant records from clinics and programs associated with the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium. METHODS AND FINDINGS: HIV-exposed infants were eligible for this retrospective cohort analysis if enrolled at <18 months at 198 clinics in 10 countries across 5 IeDEA regions: East Africa (EA), Central Africa (CA), West Africa (WA), Southern Africa (SA), and the Caribbean, Central, and South America network (CCASAnet). We estimated cumulative incidences of DNA PCR testing, loss to follow-up (LTFU), HIV diagnosis, and death through 24 months of age using proportional subdistribution hazard models accounting for competing risks. Competing risks were transfer, care withdrawal, and confirmation of negative HIV status, along with LTFU and death, when not the outcome of interest. In CA and EA, we quantified associations between maternal/infant characteristics and each outcome. A total of 82,067 infants (47,300 EA, 10,699 CA, 6,503 WA, 15,770 SA, 1,795 CCASAnet) born from 1997 to 2021 were included. Maternal antiretroviral therapy (ART) use during pregnancy ranged from 65·6% (CCASAnet) to 89·5% (EA), with improvements in all regions over time. Twenty-four-month cumulative incidences varied widely across regions, ranging from 12·3% (95% confidence limit [CL], 11·2%,13·5%) in WA to 94·8% (95% CL, 94·6%,95·1%) in EA for DNA PCR testing; 56·2% (95% CL, 55·2%,57·1%) in EA to 98·5% (95% CL, 98·3%,98·7%) in WA for LTFU; 1·9% (95% CL, 1·6%,2·3%) in WA to 10·3% (95% CL, 9·7%,10·9%) in EA for HIV diagnosis; and 0·5% (95% CL, 0·2%,1·0%) in CCASAnet to 4·7% (95% CL, 4·4%,5·0%) in EA for death. Although infant retention did not improve, HIV diagnosis and death decreased over time, and in EA, the cumulative incidence of HIV diagnosis decreased substantially, declining to 2·9% (95% CL, 1·5%,5·4%) in 2020. Maternal ART was associated with decreased infant mortality (subdistribution hazard ratio [sdHR], 0·65; 95% CL, 0·47,0·91 in EA, and sdHR, 0·51; 95% CL, 0·36,0·74 in CA) and HIV diagnosis (sdHR, 0·40; 95% CL, 0·31,0·50 in EA, and sdHR, 0·41; 95% CL, 0·31,0·54 in CA). Study limitations include potential misclassification of outcomes in real-world service delivery data and possible nonrepresentativeness of IeDEA sites and the population of HIV-exposed infants they serve. CONCLUSIONS: While there was marked regional and temporal heterogeneity in clinical and programmatic outcomes, infant LTFU was high across all regions and time periods. Further efforts are needed to keep HIV-exposed infants in care to receive essential services to reduce HIV infection and mortality.

Factors associated with HIV viral suppression among children and adults receiving antiretroviral therapy in Malawi in 2021: Evidence from the Laboratory Management Information System.

OBJECTIVE: To describe the prevalence of HIV viral suppression and assess the factors associated with HIV viral suppression among persons receiving antiretroviral therapy (ART) in Malawi in 2021. METHODS: Implementation study using routinely collected patient-level HIV RNA-PCR test result data extracted from the national Laboratory Management Information System (LIMS) database managed by the Department of HIV/AIDS in 2021. We calculated frequencies, proportions and odds ratios (OR) of HIV viral suppression with their associated 95% confidence intervals (95%CIs). We performed a random-effects logistic regression to determine the risk factors associated with HIV viral suppression among ART patients, controlling for the spatial autocorrelation between districts and adjusting for other variables. RESULTS: We evaluated 515,797 adults and children receiving ART and having a viral load test in 2021. Of these, 92.8% had HIV viral suppression. ART patients living in urban areas had lower likelihood of HIV viral suppression than those living in rural areas (adjusted OR [aOR] = 0.95, 95%CI: 0.92-0.99, p = 0.01). There was an increasing trend in HIV viral suppression with increasing ART duration. Routine VL monitoring samples were 39% more likely to have suppressed VL values than confirmatory HIV VL monitoring samples (aOR = 1.39; 95%CI: 1.34-1.43, p < 0.001). CONCLUSION: This is the first national analysis of Malawi HIV VL data from LIMS. Our findings show the need to particularly consider the urban residents, those below 20 years, males, those on ART for less than a year as well as those on specific ARV regimens in order to persistently suppress HIV VL and consequently achieve the goal of achieving HIV VL suppression by 2030.

Access to Social Protection by People Living with, at Risk of, or Affected by HIV in Eswatini, Malawi, Tanzania, and Zambia: Results from Population-Based HIV Impact Assessments.

We aimed to measure social protection coverage among the general population, women and men living with HIV (WLHIV, MLHV), female and male sex workers (FSW, MSW), men who have sex with men (MSM), adolescent girls young women (AGYW), and orphans vulnerable children (OVC) in Eswatini, Malawi, Tanzania, and Zambia. We used Population-Based HIV Impact Assessment data. We operationalised social protection benefits as external economic support from private and public sources to the household in the last three or 12 months. We estimated survey-weighted proportions and 95% confidence intervals (CI) for each population receiving social protection benefits. The sample size ranged from 10,233 adults ages 15-59 years in Eswatini to 29,638 in Tanzania. In the surveyed countries, social protection coverage among the general population was lower than the global average of 45%, ranging from 7.7% (95% CI 6.7%-8.8%) in Zambia to 39.6% (95% CI 36.8%-42.5%) in Eswatini. In Malawi and Zambia, social protection coverage among OVC, AGYW, SW, MSM, and people living with HIV (PLHIV) was similar to the general population. In Eswatini, more AGWY reported receiving social projection benefits than older women and more men not living with HIV reported receiving social protection benefits than MLHIV. In Tanzania, more WLHIV than women not living with HIV, MLHIV than men not living with HIV, and FSW than women who were not sex workers reported receiving social protection benefits. More data on access to social protection benefits by PLHIV or affected by HIV are needed to estimate better their social protection coverage.

Facing the quality of life: physical illness, anxiety, and depression symptoms among people living with HIV in rural Zambia - a cross-sectional study.

Widespread access to ART has not improved the quality of life (QoL) for people living with HIV (PLHIV). We used the United Nations Disability project (UNPRPD) evaluation data to examine how physical illness, anxiety, and depression shape the QoL of PLHIV in households receiving the social cash transfers safety nets in Luapula, Zambia. We explored associations between each outcome - physical illness, anxiety, depression symptoms - and age, gender, poverty, hunger and disability, using univariable and multivariable regressions. We adjusted p-values for multiple hypothesis testing with sharpened Qs. The sample comprised 1925 respondents 16-55 years old, median age 31 (IQR 22-42 years), majority women (n = 1514, 78.6%). Two-thirds (1239, 64.4%) reported having a physical illness, a third (671, 34.9%) anxiety, and nine per cent (366) depression symptoms. More HIV positive people had a disability (34.6%, 53 versus 28.3%, 502; Q = 0.033), were physically ill (72.5%, 111 versus 63.7%, 1128; Q = 0.011), and two-fold (aOR 1.97 95% CI 1.31-2.94) more likely to report depression symptoms than HIV negative peers. Food insecurity and disability among PLHIV may worsen their physical illnesses, anxiety, depression symptoms, and other QoL domains. More research on the quality of life of PLHIV in poverty is required.

Women with disabilities in hearing: the last mile in the elimination of mother-to-child transmission of HIV - a cross-sectional study from Zambia.

This article explored the differences in HIV testing in the elimination of mother-to-child transmission of HIV (EMTCT) between women with and without disabilities aged 16-55 years, reported being pregnant and receiving the social cash transfers (SCT) social safety nets in Luapula province, Zambia. We tested for associations between HIV testing in EMTCT and disability using logistic regression analyses. We calculated a functional score for each woman to determine if they had mild, moderate or severe difficulties and controlled for age, intimate partner sexual violence, and the SCT receipt. Of 1692 women, 29.8% (504) reported a disability, 724 (42.8%) mild, 203 (12.0%) moderate, and 83 (4.9%) severe functional difficulties (adjusted odds ratio [aOR] 1.33; 95% confidence interval [CI] 1.04-1.70). Women with moderate (aOR 2.04; 95% CI 1.44-2.88) or mild difficulties (aOR 1.66; 95% CI 1.32-2.08) or with a disability in cognition (aOR 1.67 95% CI 1.22-2.29) reported testing more for HIV than women without disabilities; Women with a disability in hearing (aOR 0.36 CI 0.16-0.80) reported testing less for HIV. Disability is common among women receiving the SCT in the study area accessing HIV testing in the EMTCT setting. HIV testing in EMTCT is challenging for women with disabilities in hearing.

Evidence-based Definition for Extensively Drug-Resistant Tuberculosis.

Rationale: Until 2020, extensively drug-resistant tuberculosis (XDR-TB) was defined as TB with resistance to rifampicin and isoniazid (multidrug-resistant TB [MDR-TB]), any fluoroquinolone (FQ), and any second-line injectable drug (SLID). In 2019, the World Health Organization issued new recommendations for treating patients with drug-resistant TB, substantially limiting the role of SLIDs in MDR-TB treatment and thus putting the definition of XDR-TB into question. Objectives: To propose an up-to-date definition for XDR-TB. Methods: We used a large data set to assess treatment outcomes for patients with MDR-TB exposed to any type of longer regimen. We included patients with bacteriologically confirmed MDR-TB and known FQ and SLID resistance results. We performed logistic regression to estimate the adjusted odds ratios (aORs) for an unfavorable treatment outcome (failure, relapse, death, loss to follow-up), and estimates were stratified by the resistance pattern (FQ and/or SLID) and group A drug use (moxifloxacin/levofloxacin, linezolid, and/or bedaquiline). Measurements and Main Results: We included 11,666 patients with MDR-TB; 4,653 (39.9%) had an unfavorable treatment outcome. Resistance to FQs increased the odds of an unfavorable treatment outcome (aOR, 1.91; 95% confidence interval [CI], 1.63-2.23). Administration of bedaquiline and/or linezolid improved treatment outcomes regardless of resistance to FQs and/or SLIDs. Among patients with XDR-TB, compared with persons receiving no group A drug, aORs for an unfavorable outcome were 0.37 (95% CI, 0.20-0.69) with linezolid only, 0.40 (95% CI, 0.21-0.77) with bedaquiline only, and 0.21 (95% CI, 0.12-0.38) with both. Conclusions: Our study supports a new definition of XDR-TB as MDR-TB and additional resistance to FQ plus bedaquiline and/or linezolid and helps assess the adequacy of this definition for surveillance and treatment choice.

Leveraging human resources for outbreak analysis: lessons from an international collaboration to support the sub-Saharan African COVID-19 response.

Emerging infectious diseases are a growing threat in sub-Saharan African countries, but the human and technical capacity to quickly respond to outbreaks remains limited. Here, we describe the experience and lessons learned from a joint project with the WHO Regional Office for Africa (WHO AFRO) to support the sub-Saharan African COVID-19 response.In June 2020, WHO AFRO contracted a number of consultants to reinforce the COVID-19 response in member states by providing actionable epidemiological analysis. Given the urgency of the situation and the magnitude of work required, we recruited a worldwide network of field experts, academics and students in the areas of public health, data science and social science to support the effort. Most analyses were performed on a merged line list of COVID-19 cases using a reverse engineering model (line listing built using data extracted from national situation reports shared by countries with the Regional Office for Africa as per the IHR (2005) obligations). The data analysis platform The Renku Project ( https://renkulab.io ) provided secure data storage and permitted collaborative coding.Over a period of 6 months, 63 contributors from 32 nations (including 17 African countries) participated in the project. A total of 45 in-depth country-specific epidemiological reports and data quality reports were prepared for 28 countries. Spatial transmission and mortality risk indices were developed for 23 countries. Text and video-based training modules were developed to integrate and mentor new members. The team also began to develop EpiGraph Hub, a web application that automates the generation of reports similar to those we created, and includes more advanced data analyses features (e.g. mathematical models, geospatial analyses) to deliver real-time, actionable results to decision-makers.Within a short period, we implemented a global collaborative approach to health data management and analyses to advance national responses to health emergencies and outbreaks. The interdisciplinary team, the hands-on training and mentoring, and the participation of local researchers were key to the success of this initiative.

Hospital outcomes of community-acquired COVID-19 versus influenza: Insights from the Swiss hospital-based surveillance of influenza and COVID-19.

BackgroundSince the onset of the COVID-19 pandemic, the disease has frequently been compared with seasonal influenza, but this comparison is based on little empirical data.AimThis study compares in-hospital outcomes for patients with community-acquired COVID-19 and patients with community-acquired influenza in Switzerland.MethodsThis retrospective multi-centre cohort study includes patients > 18 years admitted for COVID-19 or influenza A/B infection determined by RT-PCR. Primary and secondary outcomes were in-hospital mortality and intensive care unit (ICU) admission for patients with COVID-19 or influenza. We used Cox regression (cause-specific and Fine-Gray subdistribution hazard models) to account for time-dependency and competing events with inverse probability weighting to adjust for confounders.ResultsIn 2020, 2,843 patients with COVID-19 from 14 centres were included. Between 2018 and 2020, 1,381 patients with influenza from seven centres were included; 1,722 (61%) of the patients with COVID-19 and 666 (48%) of the patients with influenza were male (p < 0.001). The patients with COVID-19 were younger (median 67 years; interquartile range (IQR): 54-78) than the patients with influenza (median 74 years; IQR: 61-84) (p < 0.001). A larger percentage of patients with COVID-19 (12.8%) than patients with influenza (4.4%) died in hospital (p < 0.001). The final adjusted subdistribution hazard ratio for mortality was 3.01 (95% CI: 2.22-4.09; p < 0.001) for COVID-19 compared with influenza and 2.44 (95% CI: 2.00-3.00, p < 0.001) for ICU admission.ConclusionCommunity-acquired COVID-19 was associated with worse outcomes compared with community-acquired influenza, as the hazards of ICU admission and in-hospital death were about two-fold to three-fold higher.

Geospatial model of COVID-19 spreading and vaccination with event Gillespie algorithm.

We have developed a mathematical model and stochastic numerical simulation for the transmission of COVID-19 and other similar infectious diseases that accounts for the geographic distribution of population density, detailed down to the level of location of individuals, and age-structured contact rates. Our analytical framework includes a surrogate model optimization process to rapidly fit the parameters of the model to the observed epidemic curves for cases, hospitalizations, and deaths. This toolkit (the model, the simulation code, and the optimizer) is a useful tool for policy makers and epidemic response teams, who can use it to forecast epidemic development scenarios in local settings (at the scale of cities to large countries) and design optimal response strategies. The simulation code also enables spatial visualization, where detailed views of epidemic scenarios are displayed directly on maps of population density. The model and simulation also include the vaccination process, which can be tailored to different levels of efficiency and efficacy of different vaccines. We used the developed framework to generate predictions for the spread of COVID-19 in the canton of Geneva, Switzerland, and validated them by comparing the calculated number of cases and recoveries with data from local seroprevalence studies.

Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018-2020.

Despite its critical role in containing outbreaks, the efficacy of contact tracing, measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of contact tracing by applying unilist capture-recapture methods on data from the 2018-2020 outbreak of Ebola virus disease in the Democratic Republic of the Congo. To compute sensitivity, we applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved case-patients with any contacts and infected contacts. Geometric distributions were the best-fitting models. Our results indicate that contact tracing efforts identified almost all (n = 792, 99%) of case-patients with any contacts but only half (n = 207, 48%) of case-patients with infected contacts, suggesting that contact tracing efforts performed well at identifying contacts during the listing stage but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the ongoing coronavirus pandemic.

Evaluation of Early Warning, Alert and Response System for Ebola Virus Disease, Democratic Republic of the Congo, 2018-2020.

The 10th and largest Ebola virus disease epidemic in the Democratic Republic of the Congo (DRC) was declared in North Kivu Province in August 2018 and ended in June 2020. We describe and evaluate an Early Warning, Alert and Response System (EWARS) implemented in the Beni health zone of DRC during August 5, 2018-June 30, 2020. During this period, 194,768 alerts were received, of which 30,728 (15.8%) were validated as suspected cases. From these, 801 confirmed and 3 probable cases were detected. EWARS showed an overall good performance: sensitivity and specificity >80%, nearly all (97%) of alerts investigated within 2 hours of notification, and good demographic representativeness. The average cost of the system was US $438/case detected and US $1.8/alert received. The system was stable, despite occasional disruptions caused by political insecurity. Our results demonstrate that EWARS was a cost-effective component of the Ebola surveillance strategy in this setting.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study.

BACKGROUND: Assessing the burden of COVID-19 on the basis of medically attended case numbers is suboptimal given its reliance on testing strategy, changing case definitions, and disease presentation. Population-based serosurveys measuring anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) antibodies provide one method for estimating infection rates and monitoring the progression of the epidemic. Here, we estimate weekly seroprevalence of anti-SARS-CoV-2 antibodies in the population of Geneva, Switzerland, during the epidemic. METHODS: The SEROCoV-POP study is a population-based study of former participants of the Bus Santé study and their household members. We planned a series of 12 consecutive weekly serosurveys among randomly selected participants from a previous population-representative survey, and their household members aged 5 years and older. We tested each participant for anti-SARS-CoV-2-IgG antibodies using a commercially available ELISA. We estimated seroprevalence using a Bayesian logistic regression model taking into account test performance and adjusting for the age and sex of Geneva's population. Here we present results from the first 5 weeks of the study. FINDINGS: Between April 6 and May 9, 2020, we enrolled 2766 participants from 1339 households, with a demographic distribution similar to that of the canton of Geneva. In the first week, we estimated a seroprevalence of 4·8% (95% CI 2·4-8·0, n=341). The estimate increased to 8·5% (5·9-11·4, n=469) in the second week, to 10·9% (7·9-14·4, n=577) in the third week, 6·6% (4·3-9·4, n=604) in the fourth week, and 10·8% (8·2-13·9, n=775) in the fifth week. Individuals aged 5-9 years (relative risk [RR] 0·32 [95% CI 0·11-0·63]) and those older than 65 years (RR 0·50 [0·28-0·78]) had a significantly lower risk of being seropositive than those aged 20-49 years. After accounting for the time to seroconversion, we estimated that for every reported confirmed case, there were 11·6 infections in the community. INTERPRETATION: These results suggest that most of the population of Geneva remained uninfected during this wave of the pandemic, despite the high prevalence of COVID-19 in the region (5000 reported clinical cases over <2·5 months in the population of half a million people). Assuming that the presence of IgG antibodies is associated with immunity, these results highlight that the epidemic is far from coming to an end by means of fewer susceptible people in the population. Further, a significantly lower seroprevalence was observed for children aged 5-9 years and adults older than 65 years, compared with those aged 10-64 years. These results will inform countries considering the easing of restrictions aimed at curbing transmission. FUNDING: Swiss Federal Office of Public Health, Swiss School of Public Health (Corona Immunitas research program), Fondation de Bienfaisance du Groupe Pictet, Fondation Ancrage, Fondation Privée des Hôpitaux Universitaires de Genève, and Center for Emerging Viral Diseases.

The COVID-19 pandemic in the WHO African region: the first year (February 2020 to February 2021).

The World Health Organization African region recorded its first laboratory-confirmed coronavirus disease-2019 (COVID-19) cases on 25 February 2020. Two months later, all the 47 countries of the region were affected. The first anniversary of the pandemic occurred in a changed context with the emergence of new variants of concern (VOC) and growing COVID-19 fatigue. This study describes the epidemiological trajectory of COVID-19 in the region, summarises public health and social measures (PHSM) implemented and discusses their impact on the pandemic trajectory. As of 24 February 2021, the African region accounted for 2.5% of cases and 2.9% of deaths reported globally. Of the 13 countries that submitted detailed line listing of cases, the proportion of cases with at least one co-morbid condition was estimated at 3.3% of all cases. Hypertension, diabetes and human immunodeficiency virus (HIV) infection were the most common comorbid conditions, accounting for 11.1%, 7.1% and 5.0% of cases with comorbidities, respectively. Overall, the case fatality ratio (CFR) in patients with comorbid conditions was higher than in patients without comorbid conditions: 5.5% vs. 1.0% (P < 0.0001). Countries started to implement lockdown measures in early March 2020. This contributed to slow the spread of the pandemic at the early stage while the gradual ease of lockdowns from 20 April 2020 resulted in an upsurge. The second wave of the pandemic, which started in November 2020, coincided with the emergence of the new variants of concern. Only 0.08% of the population from six countries received at least one dose of the COVID-19 vaccine. It is critical to not only learn from the past 12 months to improve the effectiveness of the current response but also to start preparing the health systems for subsequent waves of the current pandemic and future pandemics.

Estimating the SARS-CoV2 infections detection rate and cumulative incidence in the World Health Organization African Region 10 months into the pandemic.

As of 03 January 2021, the WHO African region is the least affected by the coronavirus disease-2019 (COVID-19) pandemic, accounting for only 2.4% of cases and deaths reported globally. However, concerns abound about whether the number of cases and deaths reported from the region reflect the true burden of the disease and how the monitoring of the pandemic trajectory can inform response measures.We retrospectively estimated four key epidemiological parameters (the total number of cases, the number of missed cases, the detection rate and the cumulative incidence) using the COVID-19 prevalence calculator tool developed by Resolve to Save Lives. We used cumulative cases and deaths reported during the period 25 February to 31 December 2020 for each WHO Member State in the region as well as population data to estimate the four parameters of interest. The estimated number of confirmed cases in 42 countries out of 47 of the WHO African region included in this study was 13 947 631 [95% confidence interval (CI): 13 334 620-14 635 502] against 1 889 512 cases reported, representing 13.5% of overall detection rate (range: 4.2% in Chad, 43.9% in Guinea). The cumulative incidence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was estimated at 1.38% (95% CI: 1.31%-1.44%), with South Africa the highest [14.5% (95% CI: 13.9%-15.2%)] and Mauritius [0.1% (95% CI: 0.099%-0.11%)] the lowest. The low detection rate found in most countries of the WHO African region suggests the need to strengthen SARS-CoV-2 testing capacities and adjusting testing strategies.

Analysing the reported incidence of COVID-19 and factors associated in the World Health Organization African region as of 31 December 2020.

This study analysed the reported incidence of COVID-19 and associated epidemiological and socio-economic factors in the WHO African region. Data from COVID-19 confirmed cases and SARS-CoV-2 tests reported to the WHO by Member States between 25 February and 31 December 2020 and publicly available health and socio-economic data were analysed using univariate and multivariate binomial regression models. The overall cumulative incidence was 1846 cases per million population. Cape Verde (21 350 per million), South Africa (18 060 per million), Namibia (9840 per million), Eswatini (8151 per million) and Botswana (6044 per million) recorded the highest cumulative incidence, while Benin (260 per million), Democratic Republic of Congo (203 per million), Niger (141 cases per million), Chad (133 per million) and Burundi (62 per million) recorded the lowest. Increasing percentage of urban population (ß = -0.011, P = 0.04) was associated with low cumulative incidence, while increasing number of cumulative SARS-CoV-2 tests performed per 10 000 population (ß = 0.0006, P = 0.006) and the proportion of population aged 15-64 years (adjusted ß = 0.174, P < 0.0001) were associated with high COVID-19 cumulative incidence. With limited testing capacities and overwhelmed health systems, these findings highlight the need for countries to increase and decentralise testing capacities and adjust testing strategies to target most at-risk populations.

Information management practices in the WHO African Region to support response to the COVID-19 pandemic.

The rapid transmissibility of the severe acute respiratory syndrome-coronavirus-2 causing coronavirus disease-2019, requires timely dissemination of information and public health responses, with all 47 countries of the WHO African Region simultaneously facing significant risk, in contrast to the usual highly localised infectious disease outbreaks. This demanded a different approach to information management and an adaptive information strategy was implemented, focusing on data collection and management, reporting and analysis at the national and regional levels. This approach used frugal innovation, building on tools and technologies that are commonly used, and well understood; as well as developing simple, practical, highly functional and agile solutions that could be rapidly and remotely implemented, and flexible enough to be recalibrated and adapted as required. While the approach was successful in its aim of allowing the WHO Regional Office for Africa (WHO AFRO) to gather surveillance and epidemiological data, several challenges were encountered that affected timeliness and quality of data captured and reported by the member states, showing that strengthening data systems and digital capacity, and encouraging openness and data sharing are an important component of health system strengthening.

COVID-19 in the WHO African region: using risk assessment to inform decisions on public health and social measures.

Successive waves of COVID-19 transmission have led to exponential increases in new infections globally. In this study, we have applied a decision-making tool to assess the risk of continuing transmission to inform decisions on tailored public health and social measures (PHSM) using data on cases and deaths reported by Member States to the WHO Regional Office for Africa as of 31 December 2020. Transmission classification and health system capacity were used to assess the risk level of each country to guide implementation and adjustments to PHSM. Two countries out of 46 assessed met the criteria for sporadic transmission, one for clusters of cases, and 43 (93.5%) for community transmission (CT) including three with uncontrolled disease incidence (Eswatini, Namibia and South Africa). Health system response's capacities were assessed as adequate in two countries (4.3%), moderate in 13 countries (28.3%) and limited in 31 countries (64.4%). The risk level, calculated as a combination of transmission classification and health system response's capacities, was assessed at level 0 in one country (2.1%), level 1 in two countries (4.3%), level 2 in 11 countries (23.9%) and level 3 in 32 (69.6%) countries. The scale of severity ranged from 0 to 4, with 0 the lowest. CT coupled with limited response capacity resulted in a level 3 risk assessment in most countries. Countries at level 3 should be considered as priority focus for additional assistance, in order to prevent the risk rising to level 4, which may necessitate enforcing hard and costly lockdown measures. The large number of countries at level 3 indicates the need for an effective risk management system to be used as a basis for adjusting PHSM at national and sub-national levels.