Contact tracking data from the first COVID-19 pandemic wave in Shandong Province, China
Contact tracking data from the first COVID-19 pandemic wave in Shandong Province, China

Contact tracking data from the first COVID-19 pandemic wave in Shandong Province, China

In a recent study published in the latest issue of EpidemicsResearchers evaluated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission risks in different contact settings to prioritize disease control from potential superspreaders and their contacts.

Examination: Transmission Risk Variation for SARS-CoV-2 in Near Contact Settings: A Contact Tracing Study in Shandong Province, China. Image credit: elenabsl / Shutterstock


Contact tracking is a great tool for evaluating the relative transferability of SARS-CoV-2 across different settings, including households, healthcare and air travel. When combined with an accurate assessment of heterogeneity of SARS-CoV-2 infection that accounts for different duration of exposure at the individual level, it could predict the possibility of super-proliferation of events early to devise an appropriate intervention strategy.

Study design

In this study, researchers used an individual-based Bayesian transmission model for contact trace data from the first pandemic wave of coronavirus disease 2019 (COVID-19) in Shandong Province, China. They estimated the secondary attack rates (SAR) in different contact settings and evaluated the potential risk factors for infection and transmission. SARs reflect the transmissibility of a pathogen by measuring its susceptibility to contract a viral infection, including COVID-19 from an infectious person via close contact.

They collected demographic, clinical, and laboratory test data for symptomatic and asymptomatic SARS-CoV-2 infections (index cases) from municipal Centers for Disease Control and Prevention (CDC) in Jinan, Jining, and Qingdao cities in Shandong Province, China. They retrospectively retrieved the monitoring database for the study between 22 Januarynd and May 30thth, 2020.

During the study period, they identified reverse transcription-polymerase chain reaction (RT-PCR) -confirmed COVID-19 cases and tracked their close contacts who were quarantined for 14 days. In addition, the team collected theirs nasopharyngeal inoculation samples on days 1, 4, 7 and 14 for RT-PCR testing.

According to the definitions of the study case, close contacts were persons who had unprotected contact within one meter with a suspected or confirmed SARS-CoV-2 case within two days before the onset of symptoms or, if asymptomatic, the date of collection of the first RT-PCR-positive sample. A close contact group can have several primary cases, called co-primary cases.

First, the researchers calculated a raw SAR, the average of secondary cases among close contacts across all close contact groups with a single primary case. Assuming all secondary cases were infected by their primary case, they referred to it as the database SAR. However, not all secondary COVID-19 cases were infected by a single primary case, as there could also be tertiary transfers, or infection could be acquired from an external cluster. Fortunately, the Bayesian model accounted for and eliminated this discrepancy while predicting daily transmission dynamics.

The covariates of the study included age, gender, city, and occupation for each close contact, as well as the severity of each case and the symptom status during incubation and disease. The primary study results considered an average incubation period of five days and a maximum infectious period of 21 days.

Survey results

Among 97 laboratory-confirmed index cases included in the transmission modeling assay, there were eight clusters with a single primary case and two co-primary cases; in addition, there were 3158 close contacts in the remaining 81 clusters. The average size of these 89 clusters of close contact groups was 23. Overall, a primary case generated an average of 1.05 secondary cases in Shandong Province.

The ratio of women to men among primary cases and secondary cases was 65% vs. 35% and 59% vs. 41%. Compared to secondary cases, primary cases were more likely to be severe (14% vs. 5%) and less likely to be asymptomatic (6% vs. 10%).

The total databaseed SAR was 3.53%; moreover, it was the highest (8.64%) among close contacts over 60 years. Among the contact settings examined during the study, the household was associated with the highest database SAR of 10.1%, whereas air transport was associated with the lowest, 0.43%.

The estimated daily transmission probability of infected individuals transmitting the infection to close contacts during their incubation period was 0.044 in households, 0.032 in health facilities, 0.023 in workplaces, 0.004 during flights, and 0.002 in all other environments. It was slightly lower during the disease period, and the estimated relative infectivity was highest when both the incubation and the infectious period were longer.

Furthermore, the multivariate analysis showed that:

i) close contacts younger than 60 years had 36-49% lower risk of infection than those over 60 years;

ii) physicians were 65% less likely to become infected than non-medical contacts;

iii) the odds of infection were much lower during flights, odds ratio (ORs) 0.08 compared to within households; and

iv) the risk of infection in workplaces and health facilities was slightly lower, with ORs of 0.52 and 0.73, respectively.

The study model predicted the possibility of super-spread of incidents in two households and a health facility (three close contact groups), each with a single primary case.


To summarize, the estimated household SARs in Shandong, calculated for the entire infectious period of 22 days, were higher than most household transmission studies in China. SARS-CoV-2 was more transmissible in household environments than in workplaces and health facilities, and the risk of infection was much less during flights or in other contact conditions. In addition to the highest SAR, the household settings favored the highest number of secondary cases per year. primarily cases. In addition, age, medical status, and city were risk modifiers.

Simulation of transmission dynamics among close contacts of primary cases, assuming an average incubation of five days and a maximum infectious period of 22 days, showed that 64% of the cases did not generate secondary transmissions and 20% of cases resulted in 80% of secondary transmissions.

In conclusion, the study highlights that vaccination and non-pharmaceutical interventions should be prioritized for large close contact groups in household settings. While the risk of infection was lower during air travel, given the viral exposure among so many air passengers and the implication of long-distance proliferation, it also justifies preventive efforts in this context.

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