The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.

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.

Dexamethasone can reduce mortality in hospitalised COVID-19 patients needing oxygen and ventilation by 18% and 36%, respectively. Here, we estimate the potential number of lives saved and life years gained if this treatment were to be rolled out in the UK and globally, as well as the cost-effectiveness of implementing this intervention. Assuming SARS-CoV-2 exposure levels of 5% to 15%, we estimate that, for the UK, approximately 12,000 (4,250 - 27,000) lives could be saved between July and December 2020. Assuming that dexamethasone has a similar effect size in settings where access to oxygen therapies is limited, this would translate into approximately 650,000 (240,000 - 1,400,000) lives saved globally over the same time period. If dexamethasone acts differently in these settings, the impact could be less than half of this value. To estimate the full potential of dexamethasone in the global fight against COVID-19, it is essential to perform clinical research in settings with limited access to oxygen and/or ventilators, for example in low- and middle-income countries.

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 focussed on high-income settings. <br />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.<br />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, but low-income settings were 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.<br />Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions.<br />Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).

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 focussed 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, as well as 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).

Accurate population‐based data are needed on the rate, economic impact, and the long‐term outcomes of readmission among patients with cirrhosis. To examine the rates, costs, and 1‐year outcomes of patients readmitted within 30 days following their index hospitalization for complications of cirrhosis, we conducted a nationwide, population‐based cohort study involving all patients with cirrhosis in Thailand from 2009 through 2013, using data from the National Health Security Office databases, which included those from nationwide hospitalizations. Readmission was captured from hospitals at all health care levels across the country within the Universal Coverage Scheme. For the 134,038 patients hospitalized with cirrhosis, the overall 30‐day readmission rate was 17%. Common causes of readmission consisted of complications of portal hypertension (47%) and infections (17%). After adjusting for multiple covariates, predictors of 30‐day readmission included hepatocellular carcinoma (odds ratio [OR] 1.95, 95% confidence interval [CI] 1.84‐2.06), human immunodeficiency virus–related admission (OR 1.81, 95% CI 1.51‐2.17) and cholangiocarcinoma (OR 1.64, 95% CI 1.3‐2.05). In all, 2,936 deaths (13%) occurred during readmission, and an additional 14,425 deaths up to 1 year (63.5% total mortality among readmitted patients). Causes of death were mostly from liver‐related mortality. Average cost at index admission for those with a 30‐day readmission were significantly higher than those readmitted beyond 30 days or not readmitted. Conclusions: Patients hospitalized with cirrhosis complications had high rates of unscheduled 30‐day readmission. Average hospitalization costs were high, and only 36.5% of patients readmitted within 30 days survived at 1 year.

Background Key infection prevention and control measures to limit transmission of COVID-19 include social distancing, hand hygiene, use of facemasks and personal protective equipment. However, these have limited or no impact if not applied correctly through lack of knowledge, inappropriate attitude or incorrect practice. In order to maximise the impact of infection prevention and control measures on COVID-19 spread, we undertook a study to assess and improve knowledge, attitudes and practice among 119 healthcare workers and 100 general public in Thailand. The study setting was two inpatient hospitals providing COVID-19 testing and treatment. Detailed information on knowledge, attitudes and practice among the general public and healthcare workers regarding COVID-19 transmission and its prevention were obtained from a combination of questionnaires and observations. Results Knowledge of the main transmission routes, commonest symptoms and recommended prevention methods was mostly very high (> 80%) in both groups. There was lower awareness of aerosols, food and drink and pets as sources of transmission; of the correct duration for handwashing; recommended distance for social/physical distancing; and about recommended types of face coverings. Information sources most used and most trusted were the workplace, work colleagues, health workers and television. The results were used to produce a set of targeted educational videos which addressed many of these gaps with subsequent improvements on retesting in a number of areas. This included improvements in handwashing practice with an increase in the number of areas correctly washed in 65.5% of the public, and 57.9% of healthcare workers. The videos were then further optimized with feedback from participants followed by another round of retesting. Conclusions Detailed information on gaps in knowledge, attitudes and practice among the general public and healthcare workers regarding COVID-19 transmission and its prevention were obtained from a combination of questionnaires and observations. This was used to produce targeted educational videos which addressed these gaps with subsequent improvements on retesting. The resulting videos were then disseminated as a resource to aid in efforts to fight COVID-19 in Thailand and worldwide.

Objective This study aimed to assess the cost-effectiveness of COVID-19 vaccines, preferred COVID-19 vaccine profiles, and the preferred vaccination strategies in Thailand. Methods An age-structured transmission dynamic model was developed based on key local data to evaluate economic consequences, including cost and health outcome in terms of life-years (LYs) saved. We considered COVID-19 vaccines with different profiles and different vaccination strategies such as vaccinating elderly age groups (over 65s) or high-incidence groups, i.e. adults between 20 and 39 years old who have contributed to more than 60% of total COVID-19 cases in the country thus far. Analyses employed a societal perspective in a 1-year time horizon using a cost-effectiveness threshold of 160,000 THB per LY saved. Deterministic and probabilistic sensitivity analyses were performed to identify and characterize uncertainty in the model. Results COVID-19 vaccines that block infection combined with social distancing were cost-saving regardless of the target population compared to social distancing alone (with no vaccination). For vaccines that block infection, the preferred (cost-effective) strategy was to vaccinate the high incidence group. Meanwhile, COVID-19 vaccines that reduces severity (including hospitalization and mortality) were cost-effective when the elderly were vaccinated, while vaccinating the high-incidence group was not cost-effective with this vaccine type. Regardless of vaccine type, higher vaccination coverage, higher efficacy, and longer protection duration were always preferred. More so, vaccination with social distancing measures was always preferred to strategies without social distancing. Quarantine-related costs were a major cost component affecting the cost-effectiveness of COVID-19 vaccines. Conclusion COVID-19 vaccines are good value for money even in a relatively low-incidence and low-mortality setting such as Thailand, if the appropriate groups are vaccinated. The preferred vaccination strategies depend on the type of vaccine efficacy. Social distancing measures should accompany a vaccination strategy.