A conceptual model for optimizing vaccine coverage to reduce vector-borne infections in the presence of antibody-dependent enhancement

Assessing the impact of serostatus-dependent immunization on mitigating the spread of dengue virus

Dengue is the most rapidly spreading mosquito-borne disease that poses great threats to public health. We propose a compartmental model with primary and secondary infection and targeted vaccination to assess the impact of serostatus-dependent immunization on mitigating the spread of dengue virus. We derive the basic reproduction number and investigate the stability and bifurcations of the disease-free equilibrium and endemic equilibria. The existence of a backward bifurcation is proved and is used to explain the threshold dynamics of the transmission. We also carry out numerical simulations and present bifurcation diagrams to reveal rich dynamics of the model such as bi-stability of the equilibria, limit cycles, and chaos. We prove the uniform persistence and global stability of the model. Sensitivity analysis suggests that mosquito control and protection from mosquito bites are still the key measures of controlling the spread of dengue virus, though serostatus-dependent immunization is implemented. Our findings provide insightful information for public health in mitigating dengue epidemics through vaccination.

Impact of tetravalent dengue vaccination with screening, ADE, and altered infectivity on single-serotype dengue and Zika transmission

Acquired immunity to a dengue virus serotype (whether by infection or the only licensed dengue vaccine) can produce antibody-dependent enhancement (ADE) in later infections with another dengue serotype, resulting in higher viral loads and more severe symptoms such as dengue hemorrhagic fever, unless the person already has immunity to multiple dengue serotypes. Screening to confirm dengue seropositivity is therefore recommended before vaccination. Recent studies suggest that the closely-related Zika virus may also interact with dengue through ADE. This study uses a mathematical model to evaluate the likely impact of imperfect screening and dengue vaccination on the spread of both viruses in a population where only one dengue serotype circulates, although the vaccine may take against any or all of the four recognized serotypes. Analysis focuses on the reproductive numbers of the viruses. Results indicate that vaccination increases the spread of Zika through induced ADE, while its impact on the spread of dengue depends on screening specificity and serotype-specific vaccine efficacies, as well as the intensity of ADE. Numerical analysis identifies the roles played by age-in and catch-up vaccination as well as screening characteristics and prior dengue exposure.

Optimal Control of Mitigation Strategies for Dengue Virus Transmission

Dengue virus is transmitted by Aedes mosquitoes, posing threat to people's health and leading to great economic cost in many tropical and subtropical regions. We develop an ordinary differential equation model taking into account multiple strains of dengue virus. Using the model, we assess the effectiveness of human vaccination considering its waning and failure. We derive the lower bound and upper bound for the final size of the epidemic. Sensitivity analysis quantifies the impact of parameters on the basic reproduction number. Different scenarios of vaccinating humans show that it is better to vaccinate humans at early stages. We find that the cumulative number of infected humans is small when the vaccination rate is high or the waning rate is low for previously infected humans. We analyze the necessary conditions for implementing optimal control and derive the corresponding optimal solutions for mitigation dengue virus transmission by applying Pontryagin's Maximum Principle. Our findings may provide guidance for the public health authorities to implement human vaccination and other mitigation strategies.

The age distribution of mortality from novel coronavirus disease (COVID-19) suggests no large difference of susceptibility by age

Among Italy, Spain, and Japan, the age distributions of COVID-19 mortality show only small variation even though the number of deaths per country shows large variation. To understand the determinant for this situation, we constructed a mathematical model describing the transmission dynamics and natural history of COVID-19 and analyzed the dataset of mortality in Italy, Spain, and Japan. We estimated the parameter which describes the age-dependency of susceptibility by fitting the model to reported data, including the effect of change in contact patterns during the epidemics of COVID-19, and the fraction of symptomatic infections. Our study revealed that if the mortality rate or the fraction of symptomatic infections among all COVID-19 cases does not depend on age, then unrealistically different age-dependencies of susceptibilities against COVID-19 infections between Italy, Japan, and Spain are required to explain the similar age distribution of mortality but different basic reproduction numbers (R₀). Variation of susceptibility by age itself cannot explain the robust age distribution in mortality by COVID-19 infections in those three countries, however it does suggest that the age-dependencies of (i) the mortality rate and (ii) the fraction of symptomatic infections among all COVID-19 cases determine the age distribution of mortality by COVID-19.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.

Modelling the impact of antibody-dependent enhancement on disease severity of Zika virus and dengue virus sequential and co-infection

Human infections with viruses of the genus Flavivirus, including dengue virus (DENV) and Zika virus (ZIKV), are of increasing global importance. Owing to antibody-dependent enhancement (ADE), secondary infection with one Flavivirus following primary infection with another Flavivirus can result in a significantly larger peak viral load with a much higher risk of severe disease. Although several mathematical models have been developed to quantify the virus dynamics in the primary and secondary infections of DENV, little progress has been made regarding secondary infection of DENV after a primary infection of ZIKV, or DENV-ZIKV co-infection. Here, we address this critical gap by developing compartmental models of virus dynamics. We first fitted the models to published data on dengue viral loads of the primary and secondary infections with the observation that the primary infection reaches its peak much more gradually than the secondary infection. We then quantitatively show that ADE is the key factor determining a sharp increase/decrease of viral load near the peak time in the secondary infection. In comparison, our simulations of DENV and ZIKV co-infection (simultaneous rather than sequential) show that ADE has very limited influence on the peak DENV viral load. This indicates pre-existing immunity to ZIKV is the determinant of a high level of ADE effect. Our numerical simulations show that (i) in the absence of ADE effect, a subsequent co-infection is beneficial to the second virus; and (ii) if ADE is feasible, then a subsequent co-infection can induce greater damage to the host with a higher peak viral load and a much earlier peak time for the second virus, and for the second peak for the first virus.