Mobility trends provide a leading indicator of changes in SARS-CoV-2 transmission

Yao

et al. 2020

Preprint

The SARS-CoV-2 lineage carrying the amino acid change D614G has become the dominant variant in the global COVID-19 pandemic. The rapid spread of the G614 mutant suggests that it may have a transmission advantage over the D614 wildtype. Using our previous epidemiological framework to analyze COVID-19 surveillance and sequence data, we estimated that the G614 mutant is 31% (28-34%) more transmissible than the D614 wildtype. As such, interventions that were previously effective in containing or mitigating the D614 wildtype (e.g. in China, Vietnam, Thailand, etc.) might be less effective against the G614 mutant. Our framework can be readily integrated into current COVID-19 surveillance to monitor the emergence and fitness of mutant strains, such that pandemic surveillance, disease control and development of treatment and vaccines can be adjusted dynamically.

Section: ߬ ൏supporting

confidence: 92%

Empirical transmission advantage of the D614G mutant strain of SARS-CoV-2

Yao

et al. 2020

Preprint

“…Lastly, the inferred time-varying transmissibility correlated with mobility indicators as found elsewhere ( 20 , 31 ), and especially with mobility in transit stations. The mobility in transit stations could be a general indicator of economic / social activity resulting in more transmission.…”

Section: Discussionsupporting

confidence: 77%

Estimating the global reduction in transmission and rise in detection capacity of the novel coronavirus SARS-CoV-2 in early 2020

Belloir¹,

Blanquart²

2021

Epidemics

To better control the SARS-CoV-2 pandemic, it is essential to quantify the impact of control measures and the fraction of infected individuals that are detected. To this end we developed a deterministic transmission model based on the renewal equation and fitted the model to daily case and death data in the first few months of 2020 in 79 countries and states, representing 4.2 billions individuals. Based on a region-specific infection fatality ratio, we inferred the time-varying probability of case detection and the time-varying decline in transmissiblity. As a validation, the predicted total number of infected was close to that found in serosurveys; more importantly, the inferred probability of detection strongly correlated with the number of daily tests per inhabitant, with 50% detection achieved with 0.003 daily tests per inhabitants. Most of the decline in transmission was explained by the reductions in transmissibility (social distancing), which avoided 10 millions deaths in the regions studied over the first four months of 2020. In contrast, symptom-based testing and isolation of positive cases was not an efficient way to control the spread of the disease, as a large part of transmission happens before symptoms and only a small fraction of infected individuals was typically detected. The latter is explained by the limited number of tests available, and the fact that increasing test capacity often increases the probability of detection less than proportionally. Together these results suggest that little control can be achieved by symptom-based testing and isolation alone.

“…In fact, it has become apparent that individual and collective human behavior has had subtle and recognizable effects on SARS-CoV-2 transmission [ 22 – 25 ]. After the declaration of the public health emergency on January 24 and the adoption of strict control measures, we estimated a quick reduction of daily reproduction number, similar to what observed in other provinces of China [ 10 ] and elsewhere [ 26 – 29 ]. It is important to stress that the case definition changed over the course of the epidemic and, in particular, it was broadened on January 27 to include milder cases [ 30 ].…”

Section: Discussionsupporting

confidence: 76%

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

et al. 2020

In January 2020, a COVID-19 outbreak was detected in Sichuan Province of China. Six weeks later, the outbreak was successfully contained. The aim of this work is to characterize the epidemiology of the Sichuan outbreak and estimate the impact of interventions in limiting SARS-CoV-2 transmission. 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 estimated 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. 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 more cases (95% CI: 1,317–25,545).