In a recent article published in the medRxiv*preprint server, scientists characterized the effect of variation in individual infectiousness on the heterogeneity of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between households.
Background
Controlling the spread of a developing infectious disease requires an understanding of transmission. The most widely used indicator of infectiousness is the reproductive number. Furthermore, calculating the variance of individual infectiousness is crucial to guide disease control.
Previous reports suggested that the spread of many infectious diseases is highly heterogeneous (including SARS-CoV-2). However, since contact numbers are rarely counted in such techniques, those results are difficult to interpret. Additionally, household coronavirus disease 2019 (COVID-19) transmission assays offer the perfect setting to measure variation in individual infectiousness.
About the study
In the present study, the researchers sought to determine the heterogeneity of individual SARS-CoV-2 infectivity by analyzing data from households. Transmission of COVID-19 Research This research aimed to create a statistical model that could measure the diversity in individual infectiousness across households using publicly available data.
The team defined an index case of SARS-CoV-2 as infection initially discovered in a household, while secondary cases of COVID-19 were described as recognized virus-infected family contacts of the index patient. They conducted a systematic review to collect household experiments with a minimum of 30 households, providing the number of secondary patients and COVID-19 contacts in the household for each household by number of households with X cases in households of size Y.
Additionally, for each analysis, the researchers retrieved the investigation period, household contact testing coverage, case-finding techniques, circulating SARS-CoV-2 strain, and public health and social measures during the study period. In fact, the input for the modeling tests used in this work came from these data.
The scientists evaluated data from 17 COVID-19 household transmission experiments with known contact numbers conducted during periods of dominance of the ancestral strain of SARS-CoV-2. By fitting the contact numbers and baseline transmission chances in the fitted individual-based household transmission models to these data, they derived the pooled estimate. The model explained the probability of COVID-19 among household contacts based on the time elapsed since other household members contracted SARS-CoV-2 infection. Additionally, COVID-19 cases from community infections (i.e., beyond the household) or tertiary infections (infections through other household contacts rather than index cases) were allowed.
Results
The authors showed that the impact of the diversity of individual infectiousness on the heterogeneity of COVID-19 transmission in households could be estimated using household data using a modeling approach. They noted that the pooled infectiousness variance estimate from 14 analyzes showed that the 20% of most contagious patients with SARS-CoV-2 had 3.1-fold higher infectiousness than the average cases. This observation was consistent with the findings of viral spread variability.
Furthermore, according to the inferences of the study, there was a significant variation in the infectiousness of each patient with SARS-CoV-2 in the households. This variation could be attributed to both host behaviors and biological factors. Taking host behaviors into account, several contact trends, mainly by age, could be a factor in the variations in contagiousness of cases. In addition, contact pattern assessments indicated that young adults and school-age children tended to socialize with others their age.
The researchers found that fluctuating COVID-19 infectivity correlated substantially with the percentage of cases attributable to 80% transmission (p80), comparable to previous analyzes on superspreading. This inference suggests that it could be an indicator of the variation of infectiousness in the household. The secondary attack rate (SAR) and the percentage of households without infected contacts (p0) also affected the fluctuation of infectiousness.
The scientists found that relying solely on polymerase chain reaction (PCR) to check for secondary infections was associated with greater variability in infectivity. Other than these relationships, they were unable to discover any link between these statistics and the deployment of the lockdown, the method used to identify index and secondary patients, or the strain of SARS-CoV-2 that was in circulation during the study period.
Taken together, the team mentioned that household information could guide the assessment of variation in COVID-19 transmission, which was relevant to epidemic control.
Conclusions
In the current work, the authors quantified the heterogeneity of individual SARS-CoV-2 infectiousness. In addition, they discussed the possible causes of these variations, mainly the variation of viral shedding.
In summary, the researchers created a modeling strategy to estimate individual variation in SARS-CoV-2 infectivity from household information. Furthermore, the study findings show that individual infectiousness varies significantly, which is crucial for controlling epidemics.
*Important news
medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be considered conclusive, guide clinical practice/health-related behavior, or be treated as established information.
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