Background Mathematical modeling constitutes an important tool for planning robust responses to epidemics. This study was conducted to guide the Qatari national response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. The study investigated the epidemic’s time-course, forecasted health care needs, predicted the impact of social and physical distancing restrictions, and rationalized and justified easing of restrictions. Methods An age-structured deterministic model was constructed to describe SARS-CoV-2 transmission dynamics and disease progression throughout the population. Results The enforced social and physical distancing interventions flattened the epidemic curve, reducing the peaks for incidence, prevalence, acute-care hospitalization, and intensive care unit (ICU) hospitalizations by 87%, 86%, 76%, and 78%, respectively. The daily number of new infections was predicted to peak at 12 750 on May 23, and active-infection prevalence was predicted to peak at 3.2% on May 25. Daily acute-care and ICU-care hospital admissions and occupancy were forecast accurately and precisely. By October 15, 2020, the basic reproduction number R 0 had varied between 1.07-2.78, and 50.8% of the population were estimated to have been infected (1.43 million infections). The proportion of actual infections diagnosed was estimated at 11.6%. Applying the concept of R t tuning, gradual easing of restrictions was rationalized and justified to start on June 15, 2020, when R t declined to 0.7, to buffer the increased interpersonal contact with easing of restrictions and to minimize the risk of a second wave. No second wave has materialized as of October 15, 2020, five months after the epidemic peak. Conclusions Use of modeling and forecasting to guide the national response proved to be a successful strategy, reducing the toll of the epidemic to a manageable level for the health care system.

Repositioning of the global epicentre of non-optimal cholesterol NCD Risk Factor Collaboration (NCD-RisC)* High blood cholesterol is typically considered a feature of wealthy western countries 1,2. However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world 3 and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health 4,5. However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low-and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium,

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Introduction: Trust in government to take care of its citizens may affect mental health outcomes such as anxiety and depression, particularly as measures become more stringent. The study aimed to investigate the associations between stringency of COVID-19 social distancing policies and mental health outcomes, and the moderating effects of trust in government and gender. Methods: The study consisted of secondary analysis of publicly available cross sectional data from a global online survey COVID-19 survey conducted between 20 March and 7 April 2020. There were 106,497 adult participants (18 years of age and over) from 58 countries. The main outcome measures were indices for depression and worries. The exposure measure was the stringency index. The effect modifier measures were gender and trust in government. Multivariable regression was conducted to determine the three-way interaction between the exposure, modifier and outcome measures, adjusting for age, income and education. Results: The median age of participants (56.4% women) was 37 years. Women had higher worries and depression than men. The proportion of people trusting (44%) and distrusting (45%) the government was almost the same. Among those who strongly trusted the government, an increase in policy stringency was associated with an increase in worries. Among men who distrusted the government, an increase in policy stringency was associated with an increase in depression, but in distrusting women there was an inversed Ushaped association between policy stringency and both worries and depression. Once policies exceeded the 50-point mark on the stringency index, women benefited from the most stringent policies, yet men did not, particularly men who strongly trust or distrust the government. Conclusion: As the stringency of public health measures increases, so too do depression and worries. For safe and effective public health measures, governments should develop strategies to increase trust in their actions.