How Asymptomatic Transmission Influences Mitigation and Suppression Strategies during a Pandemic

Markov modeling and performance analysis of infectious diseases with asymptomatic patients

After over three years of COVID-19, it has become clear that infectious diseases are difficult to eradicate, and humans remain vulnerable under their influence in a long period. The presence of presymptomatic and asymptomatic patients is a significant obstacle to preventing and eliminating infectious diseases. However, the long-term transmission of infectious diseases involving asymptomatic patients still remains unclear. To address this issue, this paper develops a novel Markov process for infectious diseases with asymptomatic patients by means of a continuous-time level-dependent quasi-birth-and-death (QBD) process. The model accurately captures the transmission of infectious diseases by specifying several key parameters (or factors). To analyze the role of asymptomatic and symptomatic patients in the infectious disease transmission process, a simple sufficient condition for the stability of the Markov process of infectious diseases is derived using the mean drift technique. Then, the stationary probability vector of the QBD process is obtained by using RG-factorizations. A method of using the stationary probability vector is provided to obtain important performance measures of the model. Finally, some numerical experiments are presented to demonstrate the model's feasibility through analyzing COVID-19 as an example. The impact of key parameters on the system performance evaluation and the infectious disease transmission process are analyzed. The methodology and results of this paper can provide theoretical and technical support for the scientific control of the long-term transmission of infectious diseases, and we believe that they can serve as a foundation for developing more general models of infectious disease transmission.

Medical capacity investment for epidemic disease: The effects of policymaker's confidence and public trust

Due to the server bed shortage, which has raised ethical dilemmas in the earliest days of the COVID-19 crisis, medical capacity investment has become a vital decision-making issue in the attempt to contain the epidemic. Furthermore, economic strength has failed to explain the significant performance difference across countries in combatting COVID-19. Unlike common diseases, epidemic diseases add substantial unpredictability, complexity, and uncertainty to decision-making. Knowledge miscalibration on epidemiological uncertainties by policymaker's over- and underconfidence can seriously impact policymaking. Ineffective risk communication may lead to conflicting and incoherent information transmission. As a result, public reactions and attitudes could be influenced by policymakers' confidence due to the level of public trust, which eventually affects the degree to which an epidemic spreads. To uncover the impacts of policymakers' confidence and public trust on the medical capacity investment, we establish epidemic diffusion models to characterize how transmission evolves with (and without) vaccination and frame the capacity investment problem as a newsvendor problem. Our results show that if the public fully trusts the public health experts, the policymaker's behavioral bias is always harmful, but its effect on cost increment is marginal. If a policymaker's behavior induces public reactions due to public trust, both the spread of the epidemic and the overall performance will be significantly affected, but such impacts are not always harmful. Decision bias may be beneficial when policymakers are pessimistic or highly overconfident. Having an opportunity to amend initially biased decisions can debias a particular topic but has a limited cost-saving effect.

Reduction in COVID-19 Vaccine Effectiveness against SARS-CoV-2 Variants in Seoul according to Age, Sex, and Symptoms: A Test-Negative Case-Control Study

BACKGROUND

We evaluated vaccine effectiveness (VE) against infections with SARS-CoV-2 variants of concern in Seoul, the capital of the Republic of Korea, having the highest population density in the country, under real-world conditions.

METHODS

We evaluated the reduction in the effectiveness of mRNA and viral-vector COVID-19 vaccines against infection by the SARS-CoV-2 delta variant in a subpopulation from April 2021 to July 2021 who visited screening clinics in Seoul using a test-negative case-control study design. Moreover, we conducted a case-control study matching the ten-year-old age group, sex, healthcare workers, and five districts of Seoul, which are considered confounding factors.

RESULTS

The full VE in the pre-delta-dominant period was 95.0% (95% confidence interval [CI]: 91.2-97.2); however, it decreased to 61.1% (95% CI: 53.2-67.6) during the delta-dominant period. Notably, we found that COVID-19 VE was significantly decreased in individuals aged ≥80 years (52.9%, 95% CI: -9.9-79.8), men (50.6 %, 95% CI: 39.4-59.8), and asymptomatic individuals (49.8%, 95% CI: 36.5-60.3) during the widespread SARS-CoV-2 delta variant circulation.

CONCLUSIONS

Vaccine-mediated protection drastically declined during the delta-dominant period and in vulnerable groups. This study suggests the requirement for additional countermeasures, such as the administration of a booster vaccine, in vulnerable groups based on age, sex, and symptomatic manifestation.

Lower transmissibility of SARS-CoV-2 among asymptomatic cases: evidence from contact tracing data in Oslo, Norway

BACKGROUND

Asymptomatic COVID-19 cases have complicated the surveillance and tracking of the pandemic. Previous studies have estimated that 15-25% of all infectees remain asymptomatic.

METHODS

Based on contact tracing data from Oslo, Norway, we estimated transmission and susceptibility dynamics among symptomatic and asymptomatic cases and their contacts as identified by manual contact tracing between September 1, 2020, and September 1, 2021.

RESULTS

Among 27,473 indexes and 164,153 registered contacts, the secondary attack rate (SAR-14) was estimated to be 28% lower through asymptomatic exposure (13%) compared to symptomatic exposure (18%). Furthermore, those infected by asymptomatic cases were almost three times more likely to be asymptomatic compared to those infected by symptomatic cases.

CONCLUSIONS

Symptomatic cases spread the virus to a greater extent than asymptomatic, and infectees are more likely to be asymptomatic if their assumed infector was asymptomatic.

Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model

As part of ongoing efforts to contain the coronavirus disease (COVID-19) pandemic, understanding the role of asymptomatic patients in the transmission system is essential for infection control. However, the optimal approach to risk assessment and management of asymptomatic cases remains unclear. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) epidemic propagation model. The model was constructed based on epidemiological characteristics of COVID-19 in China and accounting for the heterogeneity of social contact networks. The early community outbreaks in Wuhan were reconstructed and fitted with the actual data. We used this model to assess epidemic control measures for asymptomatic cases in three dimensions. The impact of asymptomatic cases on epidemic propagation was examined based on the effective reproduction number, abnormally high transmission events, and type and structure of transmission. Management of asymptomatic cases can help flatten the infection curve. Tracing 75% of the asymptomatic cases corresponds to a 32.5% overall reduction in new cases (compared with tracing no asymptomatic cases). Regardless of population-wide measures, household transmission is higher than other types of transmission, accounting for an estimated 50% of all cases. The magnitude of tracing of asymptomatic cases is more important than the timing; when all symptomatic patients were traced, tested, and isolated in a timely manner, the overall epidemic was not sensitive to the time of implementing the measures to trace asymptomatic patients. Disease control and prevention within families should be emphasized during an epidemic. Note to Practitioners-This article addresses the urgent need to assess the risk of another COVID-19 outbreak caused by asymptomatic cases and to find the optimal, most practical approach to asymptomatic case management. Previous studies mostly focused on the clinical and statistical characteristics of asymptomatic cases; few have evaluated the impact of asymptomatic case measures using mathematical modeling at the community scale. This study proposed a Susceptible, Exposed, Infectious, No symptoms, Hospitalized and reported, Recovered, Death (SEINRHD) propagation model based on local community structures and social contact networks, according to the development characteristics and trend of COVID-19 in a Chinese community. The conclusion provides theoretical support for emergency work of relevant departments in different periods of an epidemic. In the early stages of the epidemic, timely detection and isolation of symptomatic patients should be a priority. Where there are surplus resources for epidemic prevention, the authorities should consider increasing the proportion of asymptomatic patients being traced. Epidemic prevention measures among family members should be a primary focus of attention. This combination of strategies can help reduce the rate of viral transmission and result in extinguishing the epidemic.