The COVID-19 outbreak in Sichuan, China: epidemiology and impact of interventions

Abstract

In January 2020, a COVID19 outbreak was detected in Sichuan Province of China. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of the performed interventions. We analyzed patient records for all laboratory confirmed cases reported in the province for the period of January 21 to March 16, 2020. To estimate the basic and daily reproduction numbers, we used a Bayesian framework. In addition, we estimate the number of cases averted by the implemented control strategies. The outbreak resulted in 539 confirmed cases, lasted less than two months, and no further local transmission was detected after February 27. The median age of local cases was 8 years older than that of imported cases. Severity of symptoms increased with age. We estimated R0 at 2.4 (95% CI: 1.6-3.7). The epidemic was self sustained for about 3 weeks before going below the epidemic threshold 3 days after the declaration of a public health emergency by Sichuan authorities. Our findings indicate that, were the control measures be adopted four weeks later, the epidemic could have lasted 49 days longer (95%CI: 31-68 days), causing 9,216 (95%CI: 1,317-25,545) more cases and possibly overwhelming Sichuan healthcare system.

Disease-economy trade-offs under alternative pandemic control strategies

“…The excessive costs and rebound effects are robust features of blanket lockdowns, both in our model (Fig.S4 & Fig. S7) and confirmed in previous studies, e.g., [60, 61, 11]. The rebound size in our model is also large—nearly 100% of cases averted during the blanket lockdown reoccur later on.…”

“…Broadly, four areas of study have informed the assessment of control strategies. Epidemiological studies evaluate disease dynamics and consider the heterogeneity of impacts resulting from control strategies [3, 4, 5, 6, 7, 8, 9, 10, 11, 12]. Epi-economics studies consider the micro-foundations of human behavior as drivers of the disease, as well as the costs and benefits of alternative control strategies [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23].…”

College Openings in the United States Increased Mobility and COVID-19 Incidence

“…This allowed us to estimate the effective reproduction number for each county. The effective reproduction number R ( t ) represents the mean number of secondary cases generated by a primary infector at time t (2–5). This measure is useful to track the effectiveness of performed control measures, which aims to push it below the epidemic threshold (corresponding to R ( t ) = 1).…”

“…Nonetheless, the effectiveness of college reopening policies as non-pharmaceutical interventions for mitigating the burden of COVID-19 is still disputed. Simulation-based studies have been unable to provide public health officials with conclusive recommendations, despite detailed COVID-19 transmission datasets (e.g., 19, 20)). The lack of a clear direction is mostly due to a lack of data about the college-specific details and how to harness movement as proxies for behavior and mixing patterns of the population while such strategies are in place.…”

Infection control and the prevalence, management and outcomes of SARS-CoV-2 infections in mental health wards in London, UK: lessons learned from wave 1 to wave 2

“…Another study showed that improvements in infection control and prevention measures in a mental health unit in Chengdu, China, 10 led to no COVID-19 cases, although this was in the context of very low regional COVID-19 prevalence during the study period. 11 We therefore aimed to replicate our earlier study 8 in 16 psychiatric wards to examine changes in clinical guidance, practice and outcome between the first and second COVID-19 waves in England. We collected data for older (≥65 years) in-patients and those with dementia in the same five NHS mental health trusts during the second wave of the COVID-19 pandemic in London, UK (14 December 2020 to 15 February 2021) to assess whether there were any differences in the management and treatment of SARS-CoV-2 infections, and, if so, whether these were accompanied by lower COVID-19 prevalence and better outcomes.…”