Seroprevalence of SARS-CoV-2 among Blood Donors and Changes after Introduction of Public Health and Social Measures, London, UK

We describe results of testing blood donors in London, UK, for severe acute respiratory disease coronavirus 2 (SARS-CoV-2) IgG before and after lockdown measures. Anonymized samples from donors 17–69 years of age were tested using 3 assays: Euroimmun IgG, Abbott IgG, and an immunoglobulin receptor-binding domain assay developed by Public Health England. Seroprevalence increased from 3.0% prelockdown (week 13, beginning March 23, 2020) to 10.4% during lockdown (weeks 15–16) and 12.3% postlockdown (week 18) by the Abbott assay. Estimates were 2.9% prelockdown, 9.9% during lockdown, and 13.0% postlockdown by the Euroimmun assay and 3.5% prelockdown, 11.8% during lockdown, and 14.1% postlockdown by the receptor-binding domain assay. By early May 2020, nearly 1 in 7 donors had evidence of past SARS-CoV-2 infection. Combining results from the Abbott and Euroimmun assays increased seroprevalence by 1.6%, 2.3%, and 0.6% at the 3 timepoints compared with Euroimmun alone, demonstrating the value of using multiple assays

Patient-led active tuberculosis case-finding in the Democratic Republic of the Congo

Objective To investigate the effect of using volunteer screeners in active tuberculosis case-finding in South Kivu, the Democratic Republic of the Congo, especially among groups at high risk of tuberculosis infection. Methods To identify and screen high-risk groups in remote communities, we trained volunteer screeners, mainly those who had themselves received treatment for tuberculosis or had a family history of the disease. A non-profit organization was created and screeners received training on the disease and its transmission at 3-day workshops. Screeners recorded the number of people screened, reporting a prolonged cough and who attended a clinic for testing, as well as test results. Data were evaluated every quarter during the 3-year period of the intervention (2014–2016). Findings Acceptability of the intervention was high. Volunteers screened 650434 individuals in their communities, 73418 of whom reported a prolonged cough; 50 368 subsequently attended a clinic for tuberculosis testing. Tuberculosis was diagnosed in 1 in 151 people screened, costing 0.29 United States dollars (US$) per person screened and US$ 44 per person diagnosed. Although members of high-risk groups with poorer access to health care represented only 5.1% (33 002/650 434) of those screened, they contributed 19.7% (845/4300) of tuberculosis diagnoses (1 diagnosis per 39 screened). The intervention resulted in an additional 4300 sputum-smear-positive pulmonary tuberculosis diagnoses, 42% (4 300/10 247) of the provincial total for that period. Conclusion Patient-led active tuberculosis case-finding represents a valuable complement to traditional case-finding, and should be used to assist health systems in the elimination of tuberculosis

Outbreak analytics: a developing data science for informing the response to emerging pathogens

Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them. Recent advances have led to the rise of outbreak analytics, an emerging data science focused on the technological and methodological aspects of the outbreak data pipeline, from collection to analysis, modelling and reporting to inform outbreak response. In this article, we assess the current state of the field. After laying out the context of outbreak response, we critically review the most common analytics components, their inter-dependencies, data requirements and the type of information they can provide to inform operations in real time. We discuss some challenges and opportunities and conclude on the potential role of outbreak analytics for improving our understanding of, and response to outbreaks of emerging pathogens. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control‘. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’

Social contact patterns and implications for infectious disease transmission - a systematic review and meta-analysis of contact surveys

Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focused on high-income settings. Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys, we explored how contact characteristics (number, location, duration, and whether physical) vary across income settings. Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income strata on the frequency, duration, and type of contacts individuals made. Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens and the effectiveness of different non-pharmaceutical interventions. Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1)