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Baseline nowcasting methods for handling delays in epidemiological data
Get PDFBackground Up-to-date real-time disease surveillance data can provide critical public health insights, however reporting delays can create downward bias in the latest data. Nowcasting methods designed to correct for this bias remain underused in public health practice due to their complexity, lack of tailored documentation, or technical barriers. Methodological advances in nowcasting are also hampered by the absence of standardised benchmarks for evaluating new methods. Methods To address these needs, we developed a family of nowcasting methods and an accompanying R package, baselinenowcast . We validated our method against the baseline method that was used in the German COVID-19 Nowcast Hub and on which our approach was based. Using this data, we conducted an analysis to compare different specifications of our method which were designed to address common issues in epidemiology such as weekday patterns in reporting and the ability to share estimates across different strata. We used our approach on norovirus surveillance data from the United Kingdom Health Security Agency (UKHSA) and compared the performance of three of our method specifications against three methods evaluated in a previous study. Results Our baseline method improved estimates compared to unadjusted data across all case studies. We found that the optimal choice of baseline method specification depends on context but that our default method specification performed well in a range of settings. Applied to UKHSA norovirus data, our method helped us understand the performance of the model currently used in public health practice. Conclusions Our method and software can be used both as a straightforward nowcasting method and provides a benchmark for nowcasting model development
Finding the right tool for the specific task: navigating RWE tools and checklists.
Get PDFReal-world evidence (RWE) is increasingly used to support product approvals and label expansions, as well as clinical and payer decision-making. Various tools (e.g. frameworks, checklists) have been developed to help inform and assess the robustness and quality of real-world study design and reporting. This targeted review provides a practical guide for leveraging these tools to increase awareness and utility for decision-makers. A pre-defined search strategy was applied to identify articles from PubMed. Articles published from 1 January 2020, through 4 October 2024 were included and reviewed to identify relevant tools aimed at assessing RWE study planning, reporting, or quality assessment. Key information regarding each was extracted and summarized including strengths, limitations, and included domains. 119 articles were initially identified, of which 15 were included after screening, referencing a total of 17 tools. These 17 tools varied in format and structure, ranging from detailed guidelines and templates to checklists and questionnaires. Utility and application of the tools identified in this targeted review vary across the evaluation of study planning, reporting, and quality. Selection of the appropriate tool depends on several factors including intended purpose of the tool, intended real-world study design, and the availability of study documentation
The relationship between general practice characteristics, case-mix, and secondary care attendances/admissions before and after the COVID-19 pandemic: Protocol for an OpenSAFELY cohort study.
Get PDFBackgroundHealthcare services in England experience increased pressure during winter months due to seasonal infectious diseases, increased multimorbidity, and fluctuating demand. Understanding how characteristics of general practices, and their registered patient case-mix contribute to secondary care use-particularly for Ambulatory Care Sensitive Conditions (ACSCs)-is essential for planning and resource allocation. Primary and secondary care activity also significantly changed during the COVID-19 pandemic, and not all activity-types have returned to pre-pandemic levels in the years since, making it critical to examine trends across both pre-and post-pandemic periods.MethodsOpenSAFELY-TPP was used to access linked electronic health record data, covering approximately 2,600 general practices (about 40% of all practices in England) and 26 million registered patients in England using TPP SystmOne software (2018-2025). Our analysis focused on weekly and aggregated rates of A&E attendances and hospital admissions during the flu and winter months (October to February), comparing patterns before and after the COVID-19 pandemic. Practice-level exposures included consultation rate per capita, practice size, region, and patient case-mix variables (e.g. age, sex, ethnicity, deprivation, multimorbidity). Outcomes included weekly rates of A&E attendances, total hospital admissions, and admissions for ACSCs.AnalysesWe will summarise variation in practice characteristics, registered patient sociodemographics, case-mix, and service use across time periods. Associations between exposures and outcomes will be examined using generalised linear models, with additional subgroup analyses by age distribution. Sensitivity analyses will assess alternative flu season definitions and account for holiday and extreme weather.DiscussionThis high-level descriptive study will provide valuable insights into variation in secondary care use across general practices and identify practice-level and case-mix factors that may contribute to winter pressures. The inclusion of both pre- and post-pandemic data will provide essential benchmarking data for future health system planning and further understanding of how the general practice context and patient case-mix affects hospital demand
Strengthening human papillomavirus vaccination programs through multi-country peer learning: lessons from the CHIC initiative.
Get PDFHuman papillomavirus (HPV) vaccination is a cornerstone of cervical cancer prevention, particularly in low- and middle-income countries (LMICs), where the burden of disease remains high1.
The World Health Organization (WHO) HPV Vaccine Introduction Clearing House reported that 147 countries (of 194 reporting) had fully introduced the HPV vaccine into their national schedules as of 20242. After COVID-19 pandemic disruptions, global coverage is again increasing. For 2024, the WHO reported that global complete vaccination coverage (which varies according to national schedules) was 28% among eligible girls worldwide. Among countries that have introduced vaccination, immunization programs have achieved an average 63% coverage with at least one vaccine dose in 20243. To achieve global cervical cancer elimination targets4, first, more countries, particularly highly populous countries, must introduce HPV vaccination into national schedules; second, national programs must find ways to achieve 90% vaccination coverage of girls by the age of 15 years
The Impact of the Malawi Social Cash Transfer Programme on Financial Well-Being among People with and without Disabilities: A Disaggregated Analysis of a Cluster Randomized Control Trial
Get PDFPeople with disabilities are frequently considered key target groups for social protection, given their heightened risk of poverty and exclusion. However, there is a lack of evidence on the impact of cash transfers among people with disabilities and their households. This study presents a disaggregated analysis of a cluster randomized control trial of the Malawi Social Cash Transfer (SCT) with two follow-ups. Overall, this study found that recipient households with and without members with disabilities experienced reduced poverty headcount and gap, increased total and per capita household consumption expenditures, and improved food security, with households with members with disabilities experiencing a differential impact on two of three indicators of food security. Further, SCT receipt was linked to increased participation in agricultural work among younger people with disabilities and increased participation in household work for people with mild disabilities and people without disabilities living in households with members with disabilities
Field evaluation of a rapid antigen test for mpox in the Democratic Republic of the Congo and Uganda: a multicentre, prospective, diagnostic accuracy study.
Get PDFBACKGROUND: Accurate, accessible diagnostic tests are essential for mpox outbreak control, particularly in settings with limited laboratory infrastructure. Antigen-based rapid diagnostic tests (RDTs) offer point-of-care potential, but clinical performance data remain scarce. We assessed a research-use-only RDT for detection of mpox at the point of care in two African countries. METHODS: This prospective, multicentre, diagnostic accuracy study of the research-use-only NG-Test Monkeypox antigen RDT (NG Biotech, Guipry-Messac, France) was done at 16 sites (hospitals or health-care facilities) in Uganda and DR Congo. We enrolled individuals of any age with clinically suspected mpox. Paired skin lesion swabs were collected from each participant for antigen testing at the point of care and real-time PCR testing at reference laboratories. Diagnostic accuracy of the antigen test was evaluated using PCR as the reference standard. Diagnostic performance metrics were estimated overall and stratified by country, age, and cycle threshold values. FINDINGS: Between Jan 29 and April 23, 2025, 645 participants were enrolled, of whom 641 (99%) had valid paired antigen and PCR test results and were included in the analysis. 416 (65%) of 641 participants were PCR positive. Overall RDT sensitivity was 70·4% (293 of 416 [95% CI 65·9-74·6]) and specificity was 89·3% (201 of 225 [84·6-92·7]). Sensitivity was higher in Uganda (195 of 238; 81·9% [95% CI 76·6-86·3]) than in DR Congo (98 of 178; 55·1% [47·7-62·2]) Specificity was 86·5% (90 of 104 [95% CI 78·7-91·8]) in Uganda compared with 91·7% (111 of 121 [85·5-95·5]) in DR Congo. Performance varied by age, viral load, and symptom duration. INTERPRETATION: Although performance of the NG-Test Monkeypox antigen RDT did not fully meet WHO Target Product Profile benchmarks, driven mainly by lower sensitivity in DR Congo, results in Uganda were more encouraging. Testing was successfully done under field conditions, including in areas affected by conflict and displacement. These findings should not be interpreted as supporting immediate field deployment but show the feasibility and current limitations of lesion-based antigen testing and the need for improved, validated assays. FUNDING: Global Virus Network, UK Medical Research Council, and University of St Andrews. TRANSLATIONS: For the Swahili and French translations of the abstract see Supplementary Materials section
Encrypt data using 7-zip
Get PDF7-Zip is an open source file archiver, which may be used to compress and encrypt one or more files. This tutorial explains how it may be applied in practice. First version made available on 5 April 2017. Last updated: 10 January 2025
Causal effect of severe and non-severe malaria on dyslipidemia in African Ancestry individuals: A Mendelian randomization study.
Get PDFBACKGROUND: Dyslipidemia is becoming prevalent in Africa, where malaria is endemic. Observational studies have documented the long-term protective effect of malaria on dyslipidemia; however, these study designs are prone to confounding. Therefore, we used Mendelian randomization (MR, a method robust to confounders and reverse causation) to determine the causal effect of severe malaria (SM) and the recurrence of non-severe malaria (RNM) on lipid traits.
METHOD: We performed two-sample MR using genome wide association study (GWAS) summary statistics for recurrent non-severe malaria (RNM) from a Benin cohort (N = 775) and severe malaria from the MalariaGEN dataset (N = 17,000) and lipid traits from summary-level data of a meta-analyzed African lipid GWAS (MALG, N = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (N = 13,612) and the Africa Wits-IN-DEPTH partnership for genomics studies (AWI-Gen) dataset (N = 10,603).
RESULT: No evidence of significant causal association was obtained between RNM and high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol and triglycerides. However, a notable association emerged between severe malarial anaemia (SMA) which is a subtype of severe malaria and reduced HDL-C levels, suggesting a potential subtype-specific effect. Nonetheless, we strongly believe that the small sample size likely affects our estimates, warranting cautious interpretation of these results.
CONCLUSION: Our findings challenge the hypothesis of a broad causal relationship between malaria (both severe and recurrent non-severe forms) and dyslipidemia. The isolated association with SMA highlights an intriguing area for future research. However, we believe that conducting larger studies to investigate the connection between malaria and dyslipidemia in Africa will enhance our ability to better address the burden posed by both diseases
Proposer of the vote of thanks to Cork et al. and contribution to the Discussion of ‘Methods for estimating the exposure–response curve to inform the new safety standards for fine particulate matter’
Get PDFMy concerns about the paper do not relate to the work itself (which is generally excellent), but rather they relate to the causal inference framework in which the work has been placed.
Causal inference: what’s in a name?
Since the time of John Snow, or earlier, epidemiologists have always done causal inference. Epidemiologists have successfully established causality – not with certainty, because nothing is certain in science, but “beyond reasonable doubt” – for a long list of hazards including tobacco smoking and lung cancer, asbestos and lung cancer, and LDL-cholesterol and cardiovascular disease. All of this was done without RCTs, although some already established causal associations were subsequently confirmed by RCTs
Harmonizing Multisource Data to Inform Vector-Borne Disease Risk Management Strategies.
Get PDFIn the last few decades, we have witnessed the emergence of new vector-borne diseases (VBDs), the globalization of endemic VBDs, and the urbanization of previously rural VBDs. Data harmonization forms the basis of robust decision-support systems designed to protect at-risk communities from VBD threats. Strong interdisciplinary partnerships, protocols, digital infrastructure, and capacity-building initiatives are essential for facilitating the coproduction of robust multisource data sets. This review provides a foundation for researchers and practitioners embarking on data harmonization efforts to (a) better understand the links among environmental degradation, climate change, socioeconomic inequalities, and VBD risk; (b) conduct risk assessments, health impact attribution, and projection studies; and (c) develop robust early warning and response systems. We draw upon best practices in harmonizing data for two well-studied VBDs, dengue and malaria, and provide recommendations for the evolution of research and digital technology to improve data harmonization for VBD risk management