No detectable fitness cost of infection by cell-fusing agent virus in Aedes aegypti mosquitoes.

Aedes mosquitoes are well-known vectors of arthropod-borne viruses (arboviruses). Mosquitoes are more frequently infected with insect-specific viruses (ISVs) that cannot infect vertebrates. Some ISVs interfere with arbovirus replication in mosquito vectors, which has gained attention for potential use against arbovirus transmission. Cell-fusing agent virus (CFAV), a widespread ISV, can reduce arbovirus dissemination in Ae. aegypti. However, vectorial capacity is largely governed by other parameters than pathogen load, including mosquito survival and biting behaviour. Understanding how ISVs impact these mosquito fitness-related traits is critical to assess the potential risk of using ISVs as biological agents. Here, we examined the effects of CFAV infection on Ae. aegypti mosquito fitness. We found no significant reduction in mosquito survival, blood-feeding behaviour and reproduction, suggesting that Ae. aegypti is tolerant to CFAV. The only detectable effect was a slight increase in human attraction of CFAV-infected females in one out of eight trials. Viral tolerance is beneficial for introducing CFAV into natural mosquito populations, whereas the potential increase in biting activity must be further investigated. Our results provide the first insight into the link between ISVs and Aedes mosquito fitness and highlight the importance of considering all aspects of vectorial capacity for arbovirus control using ISVs.

Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization.

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

COVID-19 risk assessment at the opening ceremony of the Tokyo 2020 Olympic Games.

The 2020 Olympic/Paralympic Games have been postponed to 2021, due to the COVID-19 pandemic. We developed a model that integrated source-environment-receptor pathways to evaluate how preventive efforts can reduce the infection risk among spectators at the opening ceremony of Tokyo Olympic Games. We simulated viral loads of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emitted from infectors through talking/coughing/sneezing and modeled temporal environmental behaviors, including virus inactivation and transfer. We performed Monte Carlo simulations to estimate the expected number of newly infected individuals with and without preventive measures, yielding the crude probability of a spectator being an infector among the 60,000 people expected to attend the opening ceremony. Two indicators, i.e., the expected number of newly infected individuals and the newly infected individuals per infector entry, were proposed to demonstrate the extent of achievable infection risk reduction levels by implementing possible preventive measures. A no-prevention scenario produced 1.5-1.7 newly infected individuals per infector entry, whereas a combination of cooperative preventive measures by organizers and the spectators achieved a 99% risk reduction, corresponding to 0.009-0.012 newly infected individuals per infector entry. The expected number of newly infected individuals was calculated as 0.005 for the combination of cooperative preventive scenarios with the crude probability of a spectator being an infector of 1 × 10-5. Based on our estimates, a combination of cooperative preventions between organizers and spectators is required to prevent a viral spread at the Tokyo Olympic/Paralympic Games. Further, under the assumption that society accepts < 10 newly infected persons traced to events held during the entire Olympic/Paralympic Games, we propose a crude probability of infectors of < 5 × 10-5 as a benchmark for the suppression of the infection. This is the first study to develop a model that can assess the infection risk among spectators due to exposure pathways at a mass gathering event.

Comparative assessment of primary and secondary infection risks in a norovirus outbreak using a household model simulation.

Diarrheal diseases can be transmitted via both primary infection due to exposures to contaminated materials from the environment and secondary infection due to person-to-person contacts. Usually, the importance of secondary infection is empirically assessed by fitting mathematical models to the epidemic curves. However, these empirical models may not be applicable to other epidemic cases because they are developed only for the target epidemics and they don't consider the detail routes of infection. In our previous study, we developed a theoretical model taking into account the various routes of infection that commonly occur in households (e.g., shaking hands, food handling, and changing diapers). This model was made flexible and applicable to any epidemics by means of adjusting model parameters. In this study, we proposed a new index "Vulnerability indicator to secondary infection (VISI)", which expressed a ratio of secondary infection to primary infection risks and calculated this index in a simulated norovirus (NoV) epidemic that involved 10,000 households. The results demonstrated that households composed of more than three members including infant(s) had much higher levels of VISI (5-45) than two-member-households with VISI (0.1-4). These results concluded that the infants were likely to be a hub of secondary infections in highly dense families and therefore careful handling of diapers was deemed indispensible in such families to effectively control the secondary infections.