Long-term levels of protection of different types of immunity against the Omicron variant: a rapid literature review.

INTRODUCTION: With the emergence of newer SARS-CoV-2 variants and their substantial effects on the levels and duration of protection against infection, an understanding of these characteristics of the protection conferred by humoral and cellular immunity can aid in the proper development and implementation of vaccine and safety guidelines. METHODS: We conducted a rapid literature review and searched five electronic databases weekly from 1 November 2021 to 30 September 2022. Studies that assessed the humoral or cellular immunity conferred by infection, vaccination or a hybrid (combination of both) in adults and risk groups (immunocompromised and older populations) were identified. Studies were eligible when they reported data on immunological assays of COVID-19 (related to vaccination and/or infection) or the effectiveness of protection (related to the effectiveness of vaccination and/or infection). RESULTS: We screened 5103 studies and included 205 studies, of which 70 provided data on the duration of protection against SARS-CoV-2 infection. The duration of protection of adaptive immunity was greatly impacted by Omicron and its subvariants: levels of protection were low by 3-6 months from exposure to infection/vaccination. Although more durable, cellular immunity also showed signs of waning by 6 months. First and second mRNA vaccine booster doses increased the levels of protection against infection and severe disease from Omicron and its subvariants but continued to demonstrate a high degree of waning over time. CONCLUSION: All humoral immunities (infection-acquired, vaccine-acquired and hybrid) waned by 3-6 months. Cellular immunity was more durable but showed signs of waning by 6 months. Hybrid immunity had the highest magnitude of protection against SARS-CoV-2 infection. Boosting may be recommended as early as 3-4 months after the last dose, especially in risk groups.

Evaluating tuberculosis treatment outcomes in Haiti from 2018 to 2019: A competing risk analysis.

Objectives: This study assesses tuberculosis (TB) treatment outcomes in Haiti. Methods: Data from drug-susceptible patients with TB (2018-2019) were analyzed using the Fine & Gray model with multiple imputation. Results: Of the 16,545 patients, 14.7% had concurrent HIV coinfection, with a 66.2% success rate. The median treatment duration was 5 months, with patients averaging 30 years (with an interquartile range of 22-42 years). The estimated hazard of achieving a successful treatment outcome decreased by 2.5% and 8.1% for patients aged 45 and 60 years, respectively, compared with patients aged 30 years. Male patients had a 6.5% lower estimated hazard of success than their female counterparts. In addition, patients coinfected with HIV experienced a 35.3% reduction in the estimated hazard of achieving a successful treatment outcome compared with those with a negative HIV serologic status. Conclusions: Integrated health care approaches should be implemented, incorporating innovative solutions, such as machine learning algorithms combined with geographic information systems and non-conventional data sources (including social media), to identify TB hotspots and high-burden households.

Factors Associated with Reliable Contact Tracing During the 2021 Ebola Virus Disease Outbreak in Guinea.

BACKGROUND: In 2021, an Ebola virus disease (EVD) outbreak was declared in Guinea, linked to persistent virus from the 2014-2016 West Africa Epidemic. This paper analyzes factors associated with contact tracing reliability (defined as completion of a 21-day daily follow-up) during the 2021 outbreak, and transitively, provides recommendations for enhancing contact tracing reliability in future. METHODS: We conducted a descriptive and analytical cross-sectional study using multivariate regression analysis of contact tracing data from 1071 EVD contacts of 23 EVD cases (16 confirmed and 7 probable). RESULTS: Findings revealed statistically significant factors affecting contact tracing reliability. Unmarried contacts were 12.76× more likely to miss follow-up than those married (OR = 12.76; 95% CI [3.39-48.05]; p < 0.001). Rural-dwelling contacts had 99% lower odds of being missed during the 21-day follow-up, compared to those living in urban areas (OR = 0.01; 95% CI [0.00-0.02]; p < 0.01). Contacts who did not receive food donations were 3× more likely to be missed (OR = 3.09; 95% CI [1.68-5.65]; p < 0.001) compared to those who received them. Contacts in health areas with a single team were 8× more likely to be missed (OR = 8.16; 95% CI [5.57-11.96]; p < 0.01) than those in health areas with two or more teams (OR = 1.00; 95% CI [1.68-5.65]; p < 0.001). Unvaccinated contacts were 30.1× more likely to be missed compared to vaccinated contacts (OR = 30.1; 95% CI [5.12-176.83]; p < 0.001). CONCLUSION: Findings suggest that contact tracing reliability can be significantly influenced by various demographic and organizational factors. Considering and understanding these factors-and where possible addressing them-may be crucial when designing and implementing contact tracing strategies during future outbreaks in low-resource settings.

The spatial spread of HIV in Malawi: An individual-based mathematical model.

Background: The prevalence of HIV varies greatly between and within countries. We aimed to build a comprehensive mathematical modelling tool capable of exploring the reasons of this heterogeneity and test its applicability by simulating the Malawian HIV epidemic. Methods: We developed a flexible individual-based mathematical model for HIV transmission that comprises a spatial representation and individual-level determinants. We tested this model by calibrating it to the HIV epidemic in Malawi and exploring whether the heterogeneity in HIV prevalence could be reproduced. We ran the model for 1975-2030 with five alternative realizations of the geographical structure and mobility: (I) no geographical structure; 28 administrative districts including (II) only permanent inter-district relocations, (III) inter-district permanent relocations and casual sexual relationships, or (IV) permanent relocations between districts and to/from abroad and inter-district casual sex; and (V) a grid of 10 × 10km2 cells, with permanent relocations and between-cell casual relationships. We assumed HIV was present in 1975 in the districts with >10 % prevalence in 2010. We calibrated the models to national and district-level prevalence estimates. Results: Reaching the national prevalence required all adults to have at least 22 casual sex acts/year until 1990. Models II, III and V reproduced the geographical heterogeneity in prevalence in 2010 to some extent if between-district relationships were excluded (Model II; 4.9 %-21.1 %). Long-distance casual partnership mixing mitigated the differences in prevalence substantially (range across districts 4.1%-18.9 % in 2010 in Model III; 4.0%-17.6 % in Model V); with international migration the differences disappeared (Model IV; range across districts 6.9%-13.3 % in 2010). National prevalence decreased to 5 % by 2030. Conclusion: Earlier introduction of HIV into the Southern part of Malawi may cause some level of heterogeneity in HIV prevalence. Other factors such as sociobehavioural characteristics are likely to have a major impact and need investigation.

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.

Analysis of global routine immunisation coverage shows disruption and stagnation during the first two-years of the COVID-19 pandemic with tentative recovery in 2022.

Whilst it is now widely recognised that routine immunisation (RI) was disrupted by the COVID-19 pandemic in 2020, and further so in 2021, the extent of continued interruptions in 2022 and/or rebounds to previous trends remains unclear. We modelled country-specific RI trends using validated estimates of national coverage from the World Health Organisation and United Nation Children's Fund for 182 countries (accounting for > 97% of children globally), to project expected diphtheria, tetanus, and pertussis-containing vaccine first-dose (DTP1), third-dose (DTP3) and measles-containing vaccine first-dose (MCV1) coverage for 2020-2022 based on pre-pandemic trends (from 2000 to 2019). We provide further evidence of peak pandemic immunisation disruption in 2021, followed by tentative recovery in 2022. We report a 3.4% (95 %CI: [2.5%; 4.4%]) decline in global DTP3 coverage in 2021 compared to 2000-2019 trends, from an expected 89.8% to reported 86.4%. This coverage gap reduced to a 2.7% (95 %CI: [1.8%; 3.6%]) decline in 2022, with reported coverage rising to 87.2%. Similar results were seen for DTP1 and MCV1. Whilst partial rebounds are encouraging, global coverage decline translates to a 17-year setback in RI to 2005 levels, and the majority of countries retain coverage at or lower than pre-pandemic levels. The Americas, Africa, and Asia were the most impacted regions; and low- and middle-income countries the most affected income groups. The number of annual Zero Dose (ZD) children - indicating those receiving no immunisations - increased from 12.1 million (M) globally in 2019 to a peak of 16.7 M in 2021, then reduced to 13.1 M in 2022. Overall, we estimate an excess of 8.8 M ZD children cumulatively in 2020-2022 compared to pre-pandemic levels. This work can be used as an objective baseline to inform future interventions to prioritise and target interventions, and facilitate catch-up of growing populations of under- and un-immunised children.

Treatment effect of remdesivir on the mortality of hospitalised COVID-19 patients in Switzerland across different patient groups: a tree-based model analysis.

AIMS OF THE STUDY: Remdesivir has shown benefits against COVID-19. However, it remains unclear whether, to what extent, and among whom remdesivir can reduce COVID-19-related mortality. We explored whether the treatment response to remdesivir differed by patient characteristics. METHODS: We analysed data collected from a hospital surveillance study conducted in 21 referral hospitals in Switzerland between 2020 and 2022. We applied model-based recursive partitioning to group patients by the association between treatment levels and mortality. We included either treatment (levels: none, remdesivir within 7 days of symptom onset, remdesivir after 7 days, or another treatment), age and sex, or treatment only as regression variables. Candidate partitioning variables included a range of risk factors and comorbidities (and age and sex unless included in regression). We repeated the analyses using local centring to correct the results for the propensity to receive treatment. RESULTS: Overall (n = 21,790 patients), remdesivir within 7 days was associated with increased mortality (adjusted hazard ratios 1.28-1.54 versus no treatment). The CURB-65 score caused the most instability in the regression parameters of the model. When adjusted for age and sex, patients receiving remdesivir within 7 days of onset had higher mortality than those not treated in all identified eight patient groups. When age and sex were included as partitioning variables instead, the number of groups increased to 19-20; in five to six of those branches, mortality was lower among patients who received early remdesivir. Factors determining the groups where remdesivir was potentially beneficial included the presence of oncological comorbidities, male sex, and high age. CONCLUSIONS: Some subgroups of patients, such as individuals with oncological comorbidities or elderly males, may benefit from remdesivir.

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.

COVID-19 preventive social-behavioural practices and exposure to SARS-CoV-2 among residents in the city of Yaounde: Lessons from the early phase of the pandemic in Cameroon.

Non-pharmaceutical interventions remain key in mitigating the spread of SARS-CoV-2. We sought to assess COVID-19 preventive, social-behavioural practices, and SARS-CoV-2 exposure through IgG rapid tests. This was a cross-sectional survey among 971 respondents residing in 180 households within the "Cite Verte" health district of Yaounde-Cameroon, from October-November 2020. Using a structured questionnaire, data on SARS-CoV-2 preventive and social behavioural practices were collected, while exposure to SARS-CoV-2 was determined by IgG profiling. p<0.05 was considered statistically significant. Overall, 971 participants were enrolled, among whom 56.5% were females. The age group 15-29 (33.5%) and those with a secondary level of education (44.7%) were most represented. Regarding preventive/social behavioural practices, the least respected measure was "stopped work", 49.1%, while the most respected was "Respect of hygiene rules", 93.8%. Women obeyed preventive measures more than men, with 87.6% vs 81.0% adhering to the lockdown, (p = 0.005) and 95.5% vs 91.7% to hygiene rules (p = 0.017). The age range 45-64 years was the least adherent to the lockdown rule, with 75.2% (38/153), p<0.0001. Only 24.7% (73/295) and 6.1% (59/295) of the symptomatic individuals reported having sought medical consultation and Covid-19 testing respectively. In addition, up to 69.8% (555/795) felt healthcare facilities were high-risk sites for getting infected, p = 0.002. Exposure to SARS-CoV-2 by IgG positivity was 31.1% (302/971), with men recording a higher proportion of viral exposure, 51.0% (154/302), p = 0.021. After adjusting for gender, age, education, and occupation; salaried worker (p = 0.029; OR: 0.29), and trading (p = 0.001; OR: 0.23) least complied with lockdown rule. In this community of Cameroonian residents highly exposed to COVID-19, many perceived healthcare facilities as high-risk zones for SARS-CoV-2 infection and consequently did not seek medical interventions. Thus, in the context of such a pandemic, advocacy on risk communication and community engagement for health-seeking attitudes should preferentially target men and those afraid of pandemics.

Historical visit attendance as predictor of treatment interruption in South African HIV patients: Extension of a validated machine learning model.

Retention of antiretroviral (ART) patients is a priority for achieving HIV epidemic control in South Africa. While machine-learning methods are being increasingly utilised to identify high risk populations for suboptimal HIV service utilisation, they are limited in terms of explaining relationships between predictors. To further understand these relationships, we implemented machine learning methods optimised for predictive power and traditional statistical methods. We used routinely collected electronic medical record (EMR) data to evaluate longitudinal predictors of lost-to-follow up (LTFU) and temporal interruptions in treatment (IIT) in the first two years of treatment for ART patients in the Gauteng and North West provinces of South Africa. Of the 191,162 ART patients and 1,833,248 visits analysed, 49% experienced at least one IIT and 85% of those returned for a subsequent clinical visit. Patients iteratively transition in and out of treatment indicating that ART retention in South Africa is likely underestimated. Historical visit attendance is shown to be predictive of IIT using machine learning, log binomial regression and survival analyses. Using a previously developed categorical boosting (CatBoost) algorithm, we demonstrate that historical visit attendance alone is able to predict almost half of next missed visits. With the addition of baseline demographic and clinical features, this model is able to predict up to 60% of next missed ART visits with a sensitivity of 61.9% (95% CI: 61.5-62.3%), specificity of 66.5% (95% CI: 66.4-66.7%), and positive predictive value of 19.7% (95% CI: 19.5-19.9%). While the full usage of this model is relevant for settings where infrastructure exists to extract EMR data and run computations in real-time, historical visits attendance alone can be used to identify those at risk of disengaging from HIV care in the absence of other behavioural or observable risk factors.

A community-based contact isolation strategy to reduce the spread of Ebola virus disease: an analysis of the 2018-2020 outbreak in the Democratic Republic of the Congo.

INTRODUCTION: Despite tremendous progress in the development of diagnostics, vaccines and therapeutics for Ebola virus disease (EVD), challenges remain in the implementation of holistic strategies to rapidly curtail outbreaks. We investigated the effectiveness of a community-based contact isolation strategy to limit the spread of the disease in the Democratic Republic of Congo (DRC). METHODS: We did a quasi-experimental comparison study. Eligible participants were EVD contacts registered from 12 June 2019 to 18 May 2020 in Beni and Mabalako Health Zones. Intervention group participants were isolated to specific community sites for the duration of their follow-up. Comparison group participants underwent contact tracing without isolation. The primary outcome was measured as the reproduction number (R) in the two groups. Secondary outcomes were the delay from symptom onset to isolation and case management, case fatality rate (CFR) and vaccination uptake. RESULTS: 27 324 EVD contacts were included in the study; 585 in the intervention group and 26 739 in the comparison group. The intervention group generated 32 confirmed cases (5.5%) in the first generation, while the comparison group generated 87 (0.3%). However, the 32 confirmed cases arising from the intervention contacts did not generate any additional transmission (R=0.00), whereas the 87 confirmed cases arising from the comparison group generated 99 secondary cases (R=1.14). The average delay between symptom onset and case isolation was shorter (1.3 vs 4.8 days; p<0.0001), CFR lower (12.5% vs 48.4%; p=0.0001) and postexposure vaccination uptake higher (86.0% vs 56.8%; p<0.0001) in the intervention group compared with the comparison group. A significant difference was also found between intervention and comparison groups in survival rate at the discharge of hospitalised confirmed patients (87.9% vs 47.7%, respectively; p=0.0004). CONCLUSION: The community-based contact isolation strategy used in DRC shows promise as a potentially effective approach for the rapid cessation of EVD transmission, highlighting the importance of rapidly implemented, community-oriented and trust-building control strategies.

Socioeconomic inequalities in cervical precancer screening among women in Ethiopia, Malawi, Rwanda, Tanzania, Zambia and Zimbabwe: analysis of Population-Based HIV Impact Assessment surveys.

OBJECTIVES: We examined age, residence, education and wealth inequalities and their combinations on cervical precancer screening probabilities for women. We hypothesised that inequalities in screening favoured women who were older, lived in urban areas, were more educated and wealthier. DESIGN: Cross-sectional study using Population-Based HIV Impact Assessment data. SETTING: Ethiopia, Malawi, Rwanda, Tanzania, Zambia and Zimbabwe. Differences in screening rates were analysed using multivariable logistic regressions, controlling for age, residence, education and wealth. Inequalities in screening probability were estimated using marginal effects models. PARTICIPANTS: Women aged 25-49 years, reporting screening. OUTCOME MEASURES: Self-reported screening rates, and their inequalities in percentage points, with differences of 20%+ defined as high inequality, 5%-20% as medium, 0%-5% as low. RESULTS: The sample size of participants ranged from 5882 in Ethiopia to 9186 in Tanzania. The screening rates were low in the surveyed countries, ranging from 3.5% (95% CI 3.1% to 4.0%) in Rwanda to 17.1% (95% CI 15.8% to 18.5%) and 17.4% (95% CI 16.1% to 18.8%) in Zambia and Zimbabwe. Inequalities in screening rates were low based on covariates. Combining the inequalities led to significant inequalities in screening probabilities between women living in rural areas aged 25-34 years, with a primary education level, from the lowest wealth quintile, and women living in urban areas aged 35-49 years, with the highest education level, from the highest wealth quintile, ranging from 4.4% in Rwanda to 44.6% in Zimbabwe. CONCLUSIONS: Cervical precancer screening rates were inequitable and low. No country surveyed achieved one-third of the WHO's target of screening 70% of eligible women by 2030. Combining inequalities led to high inequalities, preventing women who were younger, lived in rural areas, were uneducated, and from the lowest wealth quintile from screening. Governments should include and monitor equity in their cervical precancer screening programmes.

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.

Investing in preparedness for rapid detection and control of epidemics: analysis of health system reforms and their effect on 2021 Ebola virus disease epidemic response in Guinea.

The 2014-2016 West Africa Ebola Virus Disease (EVD) Epidemic devastated Guinea's health system and constituted a public health emergency of international concern. Following the crisis, Guinea invested in the establishment of basic health system reforms and crucial legal instruments for strengthening national health security in line with the WHO's recommendations for ensuring better preparedness for (and, therefore, a response to) health emergencies. The investments included the scaling up of Integrated Disease Surveillance and Response; Joint External Evaluation of International Health Regulation capacities; National Action Plan for Health Security; Simulation Exercises; One Health platforms; creation of decentralised structures such as regional and prefectural Emergency Operation Centres; Risk assessment and hazard identification; Expanding human resources capacity; Early Warning Alert System and community preparedness. These investments were tested in the subsequent 2021 EVD outbreak and other epidemics. In this case, there was a timely declaration and response to the 2021 EVD epidemic, a lower-case burden and mortality rate, a shorter duration of the epidemic and a significant reduction in the cost of the response. Similarly, there was timely detection, response and containment of other epidemics including Lassa fever and Marburg virus disease. Findings suggest the utility of the preparedness activities for the early detection and efficient containment of outbreaks, which, therefore, underlines the need for all countries at risk of infectious disease epidemics to invest in similar reforms. Doing so promises to be not only cost-effective but also lifesaving.

Validation and Improvement of a Machine Learning Model to Predict Interruptions in Antiretroviral Treatment in South Africa.

INTRODUCTION: Machine learning algorithms are increasingly being used to inform HIV prevention and detection strategies. We validated and extended a previously developed machine learning model for patient retention on antiretroviral therapy in a new geographic catchment area in South Africa. METHODS: We compared the ability of an adaptive boosting algorithm to predict interruption in treatment (IIT) in 2 South African cohorts from the Free State and Mpumalanga and Gauteng and North West (GA/NW) provinces. We developed a novel set of predictive features for the GA/NW cohort using a categorical boosting model. We evaluated the ability of the model to predict IIT over all visits and across different periods within a patient's treatment trajectory. RESULTS: When predicting IIT, the GA/NW and Free State and Mpumalanga models demonstrated a sensitivity of 60% and 61%, respectively, able to correctly predict nearly two-thirds of all missed visits with a positive predictive value of 18% and 19%. Using predictive features generated from the GA/NW cohort, the categorical boosting model correctly predicted 22,119 of a total of 35,985 missed next visits, yielding a sensitivity of 62%, specificity of 67%, and positive predictive value of 20%. Model performance was highest when tested on visits within the first 6 months. CONCLUSIONS: Machine learning algorithms may be useful in informing tools to increase antiretroviral therapy patient retention and efficiency of HIV care interventions. This is particularly relevant in developing countries where health data systems are being strengthened to collect data on a scale that is large enough to apply novel analytical methods.

Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study.

BACKGROUND: While many countries including Kenya transitioned from sentinel surveillance to the use of routine antenatal care (ANC) data to estimate the burden of HIV, countries in Sub Saharan Africa reported several challenges of this transition, including low uptake of HIV testing and sub national / site-level differences in HIV prevalence estimates. In Kenya voluntary HIV testing is offered to all 1st ANC clients. However, some women may decline testing. We aim to predict the HIV positivity (as a proxy of prevalence) at ANC assuming 100% uptake of HIV testing and compare this to the observed positivity. METHODS: Using a cross sectional study design, we examine routine data on HIV testing among all women attending ANC in Kwale County, Kenya, for the period January 2015 to December 2019.We used a generalized estimating equation with binomial distribution to model the observed HIV prevalence as explained by HIV status ascertainment. We then used marginal standardization to predict the HIV prevalence at 100% HIV status ascertainment and make recommendations to improve the utility of ANC routine data for HIV surveillance. RESULTS: HIV testing at ANC was at 91.3%, slightly above the global target of 90%. If there was 100% HIV status ascertainment at ANC, the HIV prevalence would be 2.7% (95% CI 2.3-3.2). This was 0.3% lower than the observed prevalence. Across the yearly predictions, there was no difference between the observed and predicted values except for 2018 where the HIV prevalence was underestimated with an absolute bias of -0.2 percent. This implies missed opportunities for identifying new HIV infections in the year 2018. CONCLUSIONS: Imperfect HIV status ascertainment at ANC overestimates HIV prevalence among women attending ANC in Kwale County. However, the use of ANC routine data may underestimate the true population prevalence. There is need to address both community level and health facility level barriers to the uptake of ANC services.

COVID-19 in Switzerland real-time epidemiological analyses powered by EpiGraphHub.

Here we present the design and results of an analytical pipeline for COVID-19 data for Switzerland. It is applied to openly available data from the beginning of the epidemic in 2020 to the present day (august 2022). We analyzed the spatio-temporal patterns of the spread of SARS-CoV2 throughout the country, applying Bayesian inference to estimate population prevalence and hospitalization ratio. We also developed forecasting models to characterize the transmission dynamics for all the country's cantons taking into account their spatial correlations in COVID incidence. The two-week forecasts of new daily hospitalizations showed good accuracy, as reported herein. These analyses' raw data and live results are available on the open-source EpiGraphHub platform to support further studies.

Factors associated with the risk of HIV infection among HIV-exposed infants in Malawi: 2013-2020.

BACKGROUND: Despite the availability of individual-level data of infants accessing HIV DNA-PCR testing service, there has been little in-depth analysis of such data. Therefore, we describe trends in risk of HIV infection among Malawi's HIV-exposed infants (HEI) with DNA-PCR HIV test result from 2013 to 2020. METHODS: This is an implementation study using routinely collected patient-level HIV DNA-PCR test result data extracted from the national Laboratory Management Information System database managed by the Department of HIV/AIDS between 1 January 2013 and 30 June 2020. We calculated frequencies, proportions and odds ratio (OR) with their associated 95% CI. We performed a random-effects logistic regression to determine the risk factors associated with HIV infection in infants, controlling for the spatial autocorrelation between districts and adjusting for other variables. RESULTS: We evaluated 255 229 HEI across 750 facilities in 28 districts. The HIV DNA-PCR test was performed within 2 months in 57% of the children. The overall HIV prevalence among all tested HEI between 2013 and 2020 was 7.2% (95% CI 7.1% to 7.3%). We observed a decreasing trend in the proportion of HEI that tested HIV positive from 7.0% (95% CI 6.6% to 7.4%) in 2013 to 5.7% (95% CI 5.4% to 5.9%) in 2015 followed by an increase to 9.9% (95% CI 9.6% to 10.2%) in 2017 and thereafter a decreasing trend between 2017 (i.e. 9.72% (95%CI: 9.43-10.01)) and 2020 (i.e. 3.86% (95%CI: 3.34-4.37)). The HIV prevalence increased by age of the HEI. There was spatial heterogeneity of HIV prevalence between districts of Malawi. The prevalence of HIV was higher among the HEI from the Northern region of Malawi. CONCLUSION: The main findings of the study are that the DNA test is performed within 2 months only in 57% of the children, that the decreasing trend of HIV prevalence among HEI observed up to 2015 was followed by an increase up to 2017 and a decrease afterwards, and that the risk of HIV infection increased with age at HIV testing. We summarised spatial and temporal trends of risk of HIV infection among HEI in Malawi between 2013 and 2020. There is need to ensure that all the HEI are enrolled in HIV care by 8 weeks of age in order to further reduce the risk of HIV in this population.

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.

Investigation of and Strategies to Control the Final Cluster of the 2018-2020 Ebola Virus Disease Outbreak in the Eastern Democratic Republic of Congo.

Background: On April 10, 2020, while the independent committee of the International Health Regulation was meeting to decide whether the 10th Ebola outbreak in the Demogratic Republic of Congo still constituted a Public Health Emergency of International Concern, a new confirmed case was reported in the city of Beni, the last epicenter of the epidemic. This study aimed to understand the source of this cluster and learn from the implemented control strategies for improved response in the future. Methods: We conducted a combined epidemiological and genomic investigation to understand the origins and dynamics of transmission within this cluster and describe the strategy that successfully controlled the outbreak. Results: Eight cases were identified as belonging to this final cluster. A total of 1028 contacts were identified. Whole-genome sequencing revealed that all cases belonged to the same cluster, the closest sequence to which was identified as a case from the Beni area with symptom onset in July 2019 and a difference of just 31 nucleotides. Outbreak control measures included community confinement of high-risk contacts. Conclusions: This study illustrates the high risk of additional flare-ups in the period leading to the end-of-outbreak declaration and the importance of maintaining enhanced surveillance and confinement activities to rapidly control Ebola outbreaks.