Background: Trachoma, caused by Chlamydia trachomatis, remains the worlds leading infectious cause of blindness. Repeated ocular infection during childhood leads to scarring of the conjunctiva, in-turning of the eyelashes (trichiasis) and corneal opacity in later life. There is a growing body of evidence to suggest non-chlamydial bacteria are associated with clinical signs of trachoma, independent of C. trachomatis infection. Methods: We used deep sequencing of the V1-V3 region of the bacterial 16S rRNA gene to characterize the microbiome of the conjunctiva of 220 residents of The Gambia, 105 with healthy conjunctivae and 115 with clinical signs of trachoma in the absence of detectable C. trachomatis infection. Deep sequencing was carried out using the Roche-454 platform. Sequence data were processed and analyzed through a pipeline developed by the Human Microbiome Project. Results: The microbiome of healthy participants was influenced by age and season of sample collection with increased richness and diversity seen in younger participants and in samples collected during the dry season. Decreased diversity and an increased abundance of Corynebacterium and Streptococcus were seen in participants with conjunctival scarring compared to normal controls. Abundance of Corynebacterium was higher still in adults with scarring and trichiasis compared to adults with scarring only. Conclusions: Our results indicate that changes in the conjunctival microbiome occur in trachomatous disease; whether these are a cause or a consequence is yet unknown.

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’.

Frail older adults are heavy users of health and social care. In order to reduce the costs associated with frailty in older age groups, safe and cost-effective strategies are required that will reduce the incidence and severity of frailty. We investigated whether self-reported intensity of physical activity (sedentary, mild, moderate or vigorous) performed at least once a week can significantly reduce trajectories of frailty in older adults who are classified as non-frail at baseline (Rockwood’s Frailty Index [FI] ≤ 0.25). Multi-level growth curve modelling was used to assess trajectories of frailty in 8649 non-frail adults aged 50 and over and according to baseline self-reported intensity of physical activity. Frailty was measured in five-year age cohorts based on age at baseline (50–54; 55–59; 60–64; 65–69; 70–74; 75–79; 80+) on up to 6 occasions, providing an average of 10 years of follow-up. All models were adjusted for baseline sex, education, wealth, cohabitation, smoking, and alcohol consumption. Compared with the sedentary reference group, mild physical activity was insufficient to significantly slow the progression of frailty, moderate physical activity reduced the progression of frailty in some age groups (particularly ages 65 and above) and vigorous activity significantly reduced the trajectory of frailty progression in all older adults. Healthy non-frail older adults require higher intensities of physical activity for continued improvement in frailty trajectories.

Droplet digital PCR (ddPCR) is an emulsion PCR process that performs absolute quantitation of nucleic acids. We developed a ddPCR assay for Chlamydia trachomatis infections and found it to be accurate and precise. Using PCR mixtures containing plasmids engineered to include the PCR target sequences, we were able to quantify with a dynamic range between 0.07 and 3,160 targets/μl ( r ² = 0.9927) with >95% confidence. Using 1,509 clinical conjunctival swab samples from a population in which trachoma is endemic in Guinea Bissau, we evaluated the specificity and sensitivity of the quantitative ddPCR assay in diagnosing ocular C. trachomatis infections by comparing the performances of ddPCR and the Roche Amplicor CT/NG test. We defined ddPCR tests as positive when we had ≥95% confidence in a nonzero estimate of target load. The sensitivity of ddPCR against Amplicor was 73.3% (95% confidence interval [CI], 67.9 to 78.7%), and specificity was 99.1% (95% CI, 98.6 to 99.6%). Negative and positive predictive values were 94.6% (95% CI, 93.4 to 95.8%) and 94.5% (95% CI, 91.3 to 97.7%), respectively. Based on Amplicor CT/NG testing, the estimated population prevalence of C. trachomatis ocular infection was ∼17.5%. Receiver-operator curve analysis was used to select critical cutoff values for use in clinical settings in which a balance between higher sensitivity and specificity is required. We concluded that ddPCR is an effective diagnostic technology suitable for both research and clinical use in diagnosing ocular C. trachomatis infections.

Background: The success of a government’s COVID-19 control strategy relies on public trust and broad acceptance of response measures. We investigated public perceptions of the UK government’s COVID-19 response, focusing on the relationship between trust and perceived transparency, during the first wave (April 2020) of the COVID-19 pandemic in the United Kingdom. Methods: Anonymous survey data were collected (2020-04-06 to 2020-04-22) from 9,322 respondents, aged 20+ using an online questionnaire shared primarily through Facebook. We took an embedded-mixed-methods approach to data analysis. Missing data were imputed via multiple imputation. Binomial & multinomial logistic regression were used to detect associations between demographic characteristics and perceptions or opinions of the UK government’s response to COVID-19. Structural topic modelling (STM), qualitative thematic coding of sub-sets of responses were then used to perform a thematic analysis of topics that were of interest to key demographic groups. Results: Most respondents (95.1%) supported government enforcement of behaviour change. While 52.1% of respondents thought the government was making good decisions, differences were apparent across demographic groups, for example respondents from Scotland had lower odds of responding positively than respondents in London. Higher educational levels saw decreasing odds of having a positive opinion of the government response and decreasing household income associated with decreasing positive opinion. Of respondents who thought the government was not making good decisions 60% believed the economy was being prioritised over people and their health. Positive views on government decision-making were associated with positive views on government transparency about the COVID-19 response. Qualitative analysis about perceptions of government transparency highlighted five key themes: (1) the justification of opacity due to the condition of crisis, (2) generalised mistrust of politics, (3) concerns about the role of scientific evidence, (4) quality of government communication and (5) questions about political decision-making processes. Conclusion: Our study suggests that trust is not homogenous across communities, and that generalised mistrust, concerns about the transparent use and communication of evidence and insights into decision-making processes can affect perceptions of the government’s pandemic response. We recommend targeted community engagement, tailored to the experiences of different groups and a new focus on accountability and openness around how decisions are made in the response to the UK COVID-19 pandemic.

Objectives: We assessed whether lockdown had a disproportionate impact on physical activity behavior in groups who were, or who perceived themselves to be, at heightened risk from COVID-19. Methods: Physical activity intensity (none, mild, moderate, or vigorous) before and during the UK COVID-19 lockdown was self-reported by 9,190 adults between 2020-04-06 and 2020-04-22. Physician-diagnosed health conditions and topic composition of open-ended text on participants' coping strategies were tested for associations with changes in physical activity. Results: Most (63.9%) participants maintained their normal physical activity intensity during lockdown, 25.0% changed toward less intensive activity and 11.1% were doing more. Doing less intensive physical activity was associated with obesity (OR 1.25, 95% CI 1.08–1.42), hypertension (OR 1.25, 1.10–1.40), lung disease (OR 1.23, 1.08–1.38), depression (OR 2.05, 1.89–2.21), and disability (OR 2.13, 1.87–2.39). Being female (OR 1.25, 1.12–1.38), living alone (OR 1.20, 1.05–1.34), or without access to a garden (OR 1.74, 1.56–1.91) were also associated with doing less intensive physical activity, but being in the highest income group (OR 1.73, 1.37–2.09) or having school-age children (OR 1.29, 1.10–1.49) were associated with doing more. Younger adults were more likely to change their PA behavior compared to older adults. Structural topic modeling of narratives on coping strategies revealed associations between changes in physical activity and perceptions of personal or familial risks at work or at home. Conclusions: Policies on maintaining or improving physical activity intensity during lockdowns should consider (1) vulnerable groups of adults including those with chronic diseases or self-perceptions of being at risk and (2) the importance of access to green or open spaces in which to exercise.