The association of COVID-19 incidence with temperature, humidity, and UV radiation - A global multi-city analysis.

BACKGROUND AND AIM: The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally. METHODS: We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone. RESULTS: We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries. CONCLUSION: Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission.

Effectiveness and cost-effectiveness of a personalised self-management intervention for living with long COVID: protocol for the LISTEN randomised controlled trial.

BACKGROUND: Individuals living with long COVID experience multiple, interacting and fluctuating symptoms which can have a dramatic impact on daily living. The aim of the Long Covid Personalised Self-managemenT support EvaluatioN (LISTEN) trial is to evaluate effects of the LISTEN co-designed self-management support intervention for non-hospitalised people living with long COVID on participation in routine activities, social participation, emotional well-being, quality of life, fatigue, and self-efficacy. Cost-effectiveness will also be evaluated, and a detailed process evaluation carried out to understand how LISTEN is implemented. METHODS: The study is a pragmatic randomised effectiveness and cost-effectiveness trial in which a total of 558 non-hospitalised people with long COVID will be randomised to either the LISTEN intervention or usual care. Recruitment strategies have been developed with input from the LISTEN Patient and Public Involvement and Engagement (PPIE) advisory group and a social enterprise, Diversity and Ability, to ensure inclusivity. Eligible participants can self-refer into the trial via a website or be referred by long COVID services. All participants complete a range of self-reported outcome measures, online, at baseline, 6 weeks, and 3 months post randomisation (the trial primary end point). Those randomised to the LISTEN intervention are offered up to six one-to-one sessions with LISTEN-trained intervention practitioners and given a co-designed digital resource and paper-based book. A detailed process evaluation will be conducted alongside the trial to inform implementation approaches should the LISTEN intervention be found effective and cost-effective. DISCUSSION: The LISTEN trial is evaluating a co-designed, personalised self-management support intervention (the LISTEN intervention) for non-hospitalised people living with long COVID. The design has incorporated extensive strategies to minimise participant burden and maximise access. Whilst the duration of follow-up is limited, all participants are approached to consent for long-term follow-up (subject to additional funding being secured). TRIAL REGISTRATION: LISTEN ISRCTN36407216. Registered on 27/01/2022.

The local burden of disease during the first wave of the COVID-19 epidemic in England: estimation using different data sources from changing surveillance practices.

BACKGROUND: The COVID-19 epidemic has differentially impacted communities across England, with regional variation in rates of confirmed cases, hospitalisations and deaths. Measurement of this burden changed substantially over the first months, as surveillance was expanded to accommodate the escalating epidemic. Laboratory confirmation was initially restricted to clinical need ("pillar 1") before expanding to community-wide symptomatics ("pillar 2"). This study aimed to ascertain whether inconsistent measurement of case data resulting from varying testing coverage could be reconciled by drawing inference from COVID-19-related deaths. METHODS: We fit a Bayesian spatio-temporal model to weekly COVID-19-related deaths per local authority (LTLA) throughout the first wave (1 January 2020-30 June 2020), adjusting for the local epidemic timing and the age, deprivation and ethnic composition of its population. We combined predictions from this model with case data under community-wide, symptomatic testing and infection prevalence estimates from the ONS infection survey, to infer the likely trajectory of infections implied by the deaths in each LTLA. RESULTS: A model including temporally- and spatially-correlated random effects was found to best accommodate the observed variation in COVID-19-related deaths, after accounting for local population characteristics. Predicted case counts under community-wide symptomatic testing suggest a total of 275,000-420,000 cases over the first wave - a median of over 100,000 additional to the total confirmed in practice under varying testing coverage. This translates to a peak incidence of around 200,000 total infections per week across England. The extent to which estimated total infections are reflected in confirmed case counts was found to vary substantially across LTLAs, ranging from 7% in Leicester to 96% in Gloucester with a median of 23%. CONCLUSIONS: Limitations in testing capacity biased the observed trajectory of COVID-19 infections throughout the first wave. Basing inference on COVID-19-related mortality and higher-coverage testing later in the time period, we could explore the extent of this bias more explicitly. Evidence points towards substantial under-representation of initial growth and peak magnitude of infections nationally, to which different parts of the country contribute unequally.

SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort.

Identifying the potential for SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders and the choice of baseline time point, and show how to account for both in reinfection analysis.

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.

BACKGROUND: The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. METHODS AND FINDINGS: We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. CONCLUSIONS: These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.

A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries.

There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission.

Epidemiological versus meteorological forecasts: Best practice for linking models to policymaking

Weather forecasts, climate change projections, and epidemiological predictions all represent domains that are using forecast data to take early action for risk management. However, the methods and applications of the modeling efforts in each of these three fields have been developed and applied with little cross-fertilization. This perspective identifies best practices in each domain that can be adopted by the others, which can be used to inform each field separately as well as to facilitate a more effective combined use for the management of compound and evolving risks. In light of increased attention to predictive modeling during the COVID-19 pandemic, we identify three major areas that all three of these modeling fields should prioritize for future investment and improvement: (1) decision support, (2) conveying uncertainty, and (3) capturing vulnerability.

COVID-19 pandemic and its impact on social relationships and health.

This essay examines key aspects of social relationships that were disrupted by the COVID-19 pandemic. It focuses explicitly on relational mechanisms of health and brings together theory and emerging evidence on the effects of the COVID-19 pandemic to make recommendations for future public health policy and recovery. We first provide an overview of the pandemic in the UK context, outlining the nature of the public health response. We then introduce four distinct domains of social relationships: social networks, social support, social interaction and intimacy, highlighting the mechanisms through which the pandemic and associated public health response drastically altered social interactions in each domain. Throughout the essay, the lens of health inequalities, and perspective of relationships as interconnecting elements in a broader system, is used to explore the varying impact of these disruptions. The essay concludes by providing recommendations for longer term recovery ensuring that the social relational cost of COVID-19 is adequately considered in efforts to rebuild.

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises.

TRANSLATIONS: For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.

Exceptional Prices of Medical and Other Supplies during the COVID-19 Pandemic in Ecuador.

Shortages of essential supplies used to prevent, diagnose, and treat COVID-19 have been a global concern, and price speculation and hikes may have negatively influenced access. This study identifies variability in prices of products acquired through government-driven contracts in Ecuador during the early pandemic response, when the highest mortality rates were registered in a single day. Data were obtained from the National Public Procurement Service (SERCOP) database between March 1 and July 31, 2020. A statistical descriptive analysis was conducted to extract relevant measures for commonly purchased products, medical devices, pharmaceutical drugs, and other goods. Among the most frequently purchased products, the greatest amounts were spent on face masks (US$4.5 million), acetaminophen (US$2.2 million), and reverse transcriptase quantitative polymerase chain reaction assay kits (US$1.8 million). Prices varied greatly, depending on each individual contract and on the number of units purchased; some were exceptionally higher than their market value. Compared with 2019, the mean price of medical examination gloves increased up to 1,307%, acetaminophen 500 mg pills, up to 796%, and oxygen flasks, 30.8%. In a context of budgetary constraints that actually required an effective use of available funds, speculative price hikes may have limited patient access to health care and the protection of the general population and health care workers. COVID-19 vaccine allocations to privileged individuals have also been widely reported. Price caps and other forms of regulation, as well as greater scrutiny and transparency of government-driven purchases, and investment in local production, are warranted in Ecuador for improved infectious disease prevention.

Lifestyle, Exercise and Activity Package for People living with Progressive Multiple Sclerosis (LEAP-MS): adaptions during the COVID-19 pandemic and remote delivery for improved efficiency.

The LEAP-MS (Lifestyle, Exercise and Activity Package for People living with Progressive Multiple Sclerosis) study has developed an individualised supported self-management approach for physical activity for people with progressive multiple sclerosis (MS) and severe disability. The intervention has been evaluated in a single-arm feasibility study with embedded process evaluation. The feasibility study was due to open to recruitment during the COVID-19 2020-2021 pandemic, 1 month into the first UK-wide lockdown. We worked rapidly to implement adaptions to the trial procedures and intervention delivery that we believe are applicable to randomised controlled trials. Recruitment became predominantly via self-referral. Electronic consent was employed, with consent discussions occurring over the telephone. Registration, consent, eligibility assessment and data collection as well as the intervention (online physical activity tool) were via a secure, encrypted multi-user web-based platform for participants, physiotherapists and researchers accessible via various hardware. Physiotherapy consultations, as well as the process evaluation, were conducted remotely using video conferencing software or the telephone. A remote training package for physiotherapists and site initiations was also developed and electronic site files employed. Our adaptions are extremely topical given the COVID-19 situation, and whilst not what we had originally planned, have enabled successful delivery of the feasibility study and are relevant to conducting randomised controlled trials and meeting the needs of people with MS who are far more isolated than ever before. TRIAL REGISTRATION: ClinicalTrials.gov NCT03951181 . Registered on 15 May 2019.

Testing for SARS-CoV-2 at the core of voluntary collective isolation: Lessons from the indigenous populations living in the Amazon region in Ecuador.

Voluntary collective isolation has been proposed to be the best response to COVID-19 for indigenous populations. While the potential value of voluntary collective isolation is appealing, the feasibility of this approach needs empirical evidence to support it as the best response to protect indigenous communities from COVID-19. This paper describes our experience during SARS-CoV-2 surveillance among Waorani communities in the Ecuadorian Amazonian region, from June to September 2020. We found that self-isolation strategies failed to contain the spread of SARS-CoV-2 from main urban areas to remote and isolated comunities.

Epidemiological, socio-demographic and clinical features of the early phase of the COVID-19 epidemic in Ecuador.

The SARS-CoV-2 virus has spread rapidly around the globe. Nevertheless, there is limited information describing the characteristics and outcomes of COVID-19 patients in Latin America. We conducted a cross-sectional analysis of 9,468 confirmed COVID-19 cases reported in Ecuador. We calculated overall incidence, mortality, case fatality rates, disability adjusted life years, attack and crude mortality rates, as well as relative risk and relative odds of death, adjusted for age, sex and presence of comorbidities. A total of 9,468 positive COVID-19 cases and 474 deaths were included in the analysis. Men accounted for 55.4% (n = 5, 247) of cases and women for 44.6% (n = 4, 221). We found the presence of comorbidities, being male and older than 65 years were important determinants of mortality. Coastal regions were most affected by COVID-19, with higher mortality rates than the highlands. Fatigue was reported in 53.2% of the patients, followed by headache (43%), dry cough (41.7%), ageusia (37.1%) and anosmia (36.1%). We present an analysis of the burden of COVID-19 in Ecuador. Our findings show that men are at higher risk of dying from COVID-19 than women, and risk increases with age and the presence of comorbidities. We also found that blue-collar workers and the unemployed are at greater risk of dying. These early observations offer clinical insights for the medical community to help improve patient care and for public health officials to strengthen Ecuador's response to the outbreak.

The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories.

BACKGROUND: Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. METHODS: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. RESULTS: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity. CONCLUSION: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.