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

Co-infection of dengue and Zika viruses mutually enhances viral replication in the mosquito Aedes aegypti

BACKGROUND

The mosquito Aedes aegypti transmits two of the most serious mosquito-borne viruses, dengue virus (DENV) and Zika virus (ZIKV), which results in significant human morbidity and mortality worldwide. The quickly shifting landscapes of DENV and ZIKV endemicity worldwide raise concerns that their co-circulation through the Ae. aegypti mosquito vector could greatly exacerbate the disease burden in humans. Recent reports have indicated an increase in the number of co-infection cases in expanding co-endemic regions; however, the impact of co-infection on viral infection and the detailed molecular mechanisms remain to be defined.

METHODS

C6/36 (Aedes albopictus) cells were cultured in Dulbecco's modified Eagle medium/Mitsuhashi and Maramorosch Insect Medium (DMEM/MM) (1:1) containing 2% heat-inactivated fetal bovine serum and 1× penicillin/streptomycin solution. For virus propagation, the cells were infected with either DENV serotype 2 (DENV2) strain 16681 or ZIKV isolate Thailand/1610acTw (MF692778.1). Mosquitoes (Ae. aegypti UGAL [University of Georgia Laboratory]/Rockefeller strain) were orally infected with DENV2 and ZIKV through infectious blood-feeding.

RESULTS

We first examined viral replication activity in cells infected simultaneously, or sequentially, with DENV and ZIKV, and found interspecies binding of viral genomic transcripts to the non-structural protein 5 (NS5). When we challenged Ae. aegypti mosquitos with both DENV2 and ZIKV sequentially to probe similar interactions, virus production and vector susceptibility to infection were significantly enhanced.

CONCLUSIONS

Our results suggest that DENV2 and ZIKV simultaneously establishing infection in the Ae. aegypti mosquito vector may augment one another during replication. The data also implicate the homologous NS5 protein as a key intersection between the flaviviruses in co-infection, highlighting it as a potential target for vector control.

Novel Therapeutic Nutrients Molecules That Protect against Zika Virus Infection with a Special Note on Palmitoleate

Zika virus (ZIKV) is a Flavivirus from the Flaviviridae family and a positive-sense single strand RNA virus. ZIKV infection can cause a mild infection to the mother but can be vertically transmitted to the developing fetus, causing congenital anomalies. The prevalence of ZIKV infections was relatively insignificant with sporadic outbreaks in the Asian and African continents until 2006. However, recent epidemic in the Caribbean showed significant increased incidence of Congenital Zika Syndrome. ZIKV infection results in placental pathology which plays a crucial role in disease transmission from mother to fetus. Currently, there is no Food and Drug Administration (FDA) approved vaccine or therapeutic drug against ZIKV. This review article summarizes the recent advances on ZIKV transmission and diagnosis and reviews nutraceuticals which can protect against the ZIKV infection. Further, we have reviewed recent advances related to the novel therapeutic nutrient molecules that have been shown to possess activity against Zika virus infected cells. We also review the mechanism of ZIKV-induced endoplasmic reticulum and apoptosis and the protective role of palmitoleate (nutrient molecule) against ZIKV-induced ER stress and apoptosis in the placental trophoblasts.

The resurgence risk of COVID-19 in China in the presence of immunity waning and ADE: A mathematical modelling study

The mass vaccination program has been actively promoted since the end of 2020. However, waning immunity, antibody-dependent enhancement (ADE), and increased transmissibility of variants make the herd immunity untenable and the implementation of dynamic zero-COVID policy challenging in China. To explore how long the vaccination program can prevent China at low resurgence risk, and how these factors affect the long-term trajectory of the COVID-19 epidemics, we developed a dynamic transmission model of COVID-19 incorporating vaccination and waning immunity, calibrated using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and two doses reach 77.92% on 31 August 2021. However, despite the mass vaccination, randomly introducing infected cases in the post-vaccination period causes large outbreaks quickly with waning immunity, particularly for SARS-CoV-2 variants with higher transmissibility. The results showed that with the current vaccination program and 50% of the population wearing masks, mainland China can be protected at low resurgence risk until 8 January 2023. However, ADE and higher transmissibility for variants would significantly shorten the low-risk period by over 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequent outbreaks decrease, indicating that subsequent outbreaks boosted immunity in the population level, further indicating that follow-up vaccination programs can help mitigate or avoid the possible outbreaks. The findings revealed that the integrated effects of multiple factors: waning immunity, ADE, relaxed interventions, and higher variant transmissibility, make controlling COVID-19 challenging. We should prepare for a long struggle with COVID-19, and not entirely rely on the COVID-19 vaccine.

Temporal patterns of functional anti-dengue antibodies in dengue infected individuals with different disease outcome or infection history

Heterotypic secondary dengue virus (DENV) infection is a risk factor for the development of severe disease. To assess the contribution of the developing polyclonal humoral immune response to the course of acute infection, we have determined anti-DENV IgG titers, neutralizing antibodies, percentages of antibodies binding to DENV-infected cells and antibody‑dependent enhancement (ADE) to the infecting serotype in DENV-infected Cambodian children (n = 58), ranging from asymptomatic dengue to severe disease. The results showed that ADE titers are highest against the infecting serotype during heterotypic secondary DENV-2 infection. Moreover, IgG titers, neutralizing antibodies and ADE titers against the infecting serotype peak at D10 and are maintained until D60 after laboratory-confirmed secondary DENV infection. Anti-DENV IgG titers and the magnitude of the functional antibody response were higher in secondary DENV-infected patients compared to primary infected patients. No differences in antibody titers, neutralizing or enhancing antibodies could be observed between asymptomatic or hospitalized patients between 6 and 8 days after laboratory-confirmed DENV-1 infection. However, at this time point, the level of IgG bound to DENV-infected cells was associated with disease severity in hospitalized patients. Taken together, our data offer insights for more comprehensive interpretation of antibody response profile to natural infection and its correlation to disease outcome.

Effects of the Developing and Using a Model to Predict Dengue Risk Villages Based on Subdistrict Administrative Organization in Southern Thailand

The purpose of this study was to evaluate the effects of developing and using a model to predict dengue risk in villages and of a larval indices surveillance system for 2372 households in 10 Thai villages. A community participatory action research method was used in five steps: (1) community preparation covering all stakeholders, (2) assessment of the understanding of a dengue solution and a larval indices surveillance system, (3) development of a prediction and intervention model for dengue risk villages, (4) implementation of the model that responds to all stakeholders, and (5) evaluation of the effects of using the model. The questionnaires to assess and evaluate were validated and reliability tested. The chi-square test and Fisher's exact test were used to analyze the quantitative data collected by means of questionnaires. Thematic analysis was applied to the qualitative data collected through interviews. The results found that the model consisted of six main activities, including (1) setting team leader responsibility, (2) situation assessment, (3) prediction of the dengue risk in villages, (4) the six steps of the larval indices surveillance system, (5) the understanding of the dengue solution and the understanding of the larval indices surveillance system training program, and (6) local wisdom innovation. The effects of using the model showed a statistically significant increase in correct understanding among 932 family leaders, 109 village health volunteers, and 59 student leaders regarding dengue prevention and control (p < 0.05). The larval indices and dengue morbidity were diminished and related to the nine themes present in the community leaders' reflections and to the satisfaction of the community members. Hence, local administrative organizations should use community-based approaches as the subdistrict dengue solution innovation to reduce the dengue problem.

COVID-19 Adaptive Humoral Immunity Models: Weakly Neutralizing Versus Antibody-Disease Enhancement Scenarios

The interplay between the virus, infected cells and immune responses to SARS-CoV-2 is still under debate. By extending the basic model of viral dynamics, we propose here a formal approach to describe neutralisation versus weak (or non-)neutralisation scenarios and compare them with the possible effects of antibody-dependent enhancement (ADE). The theoretical model is consistent with the data available in the literature; we show that both weakly neutralising antibodies and ADE can result in final viral clearance or disease progression, but that the immunodynamics are different in each case. As a significant proportion of the world’s population is already naturally immune or vaccinated, we also discuss the implications for secondary infections after vaccination or in the presence of immune system dysfunctions.

Mathematical models for dengue fever epidemiology: A 10-year systematic review

Mathematical models have a long history in epidemiological research, and as the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. Mathematical models describing dengue fever epidemiological dynamics are found back from 1970. Dengue fever is a viral mosquito-borne infection caused by four antigenically related but distinct serotypes (DENV-1 to DENV-4). With 2.5 billion people at risk of acquiring the infection, it is a major international public health concern. Although most of the cases are asymptomatic or mild, the disease immunological response is complex, with severe disease linked to the antibody-dependent enhancement (ADE) - a disease augmentation phenomenon where pre-existing antibodies to previous dengue infection do not neutralize but rather enhance the new infection. Here, we present a 10-year systematic review on mathematical models for dengue fever epidemiology. Specifically, we review multi-strain frameworks describing host-to-host and vector-host transmission models and within-host models describing viral replication and the respective immune response. Following a detailed literature search in standard scientific databases, different mathematical models in terms of their scope, analytical approach and structural form, including model validation and parameter estimation using empirical data, are described and analyzed. Aiming to identify a consensus on infectious diseases modeling aspects that can contribute to public health authorities for disease control, we revise the current understanding of epidemiological and immunological factors influencing the transmission dynamics of dengue. This review provide insights on general features to be considered to model aspects of real-world public health problems, such as the current epidemiological scenario we are living in.

Developing Risk Assessment Criteria and Predicting High- and Low-Dengue Risk Villages for Strengthening Dengue Prevention Activities: Community Participatory Action Research, Thailand

Background:

Risk assessment criteria for predicting dengue outbreak must be appropriated at village levels. We aimed to develop risk dengue village prediction criteria, predict village dengue risk, and strengthen dengue prevention based on community participation.

Methods:

This participatory research conducted in Southern Thailand included the following 5 phases: (i) preparing communities in 3 districts; (ii) developing risk dengue village prediction criteria; (iii) applying computer program; (iv) predicting village dengue risk with 75 public health providers in 39 PCUs; and (v) utilizing findings to strengthen dengue prevention activities in 220 villages. Data collecting for prediction used secondary data from primary care units in the past 5 year and current year. Descriptive statistics used calculating criteria and comparing with standard level to adjust score of risk.

Results:

Risk dengue village assessment criteria had 2 aspects: dengue severity (3 factors) and dengue outbreak opportunity (3 factors). Total scores were 33 points and cut-off of 17 points for high and low dengue risks villages. All criteria were applied using computer program (http://surat.denguelim.com). Risk prediction involved stakeholder participation in 220 villages, and used for strengthening dengue prevention activities. The concept of integrated vector management included larval indices surveillance system, garbage management, larval indices level lower than the standard, community capacity activities for dengue prevention, and school-based dengue prevention. The risk prediction criteria and process mobilized villages for dengue prevention activities to decrease morbidity rate.

Conclusion:

Dengue risk assessment criteria were appropriated within the village, with its smallest unit, the household, included. The data can be utilized at village levels for evaluating dengue outbreak risks.

Human lung-on-chips: Advanced systems for respiratory virus models and assessment of immune response

Respiratory viral infections are leading causes of death worldwide. A number of human respiratory viruses circulate in all age groups and adapt to person-to-person transmission. It is vital to understand how these viruses infect the host and how the host responds to prevent infection and onset of disease. Although animal models have been widely used to study disease states, incisive arguments related to poor prediction of patient responses have led to the development of microfluidic organ-on-chip models, which aim to recapitulate organ-level physiology. Over the past decade, human lung chips have been shown to mimic many aspects of the lung function and its complex microenvironment. In this review, we address immunological responses to viral infections and elaborate on human lung airway and alveolus chips reported to model respiratory viral infections and therapeutic interventions. Advances in the field will expedite the development of therapeutics and vaccines for human welfare.

Antibody dependent enhancement: Unavoidable problems in vaccine development

In some cases, antibodies can enhance virus entry and replication in cells. This phenomenon is called antibody-dependent infection enhancement (ADE). ADE not only promotes the virus to be recognized by the target cell and enters the target cell, but also affects the signal transmission in the target cell. Early formalin-inactivated virus vaccines such as aluminum adjuvants (RSV and measles) have been shown to induce ADE. Although there is no direct evidence that there is ADE in COVID-19, this potential risk is a huge challenge for prevention and vaccine development. This article focuses on the virus-induced ADE phenomenon and its molecular mechanism. It also summarizes various attempts in vaccine research and development to eliminate the ADE phenomenon, and proposes to avoid ADE in vaccine development from the perspective of antigens and adjuvants.

COVID-19: Progress in diagnostics, therapy and vaccination

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has recently become a pandemic. As the sudden emergence and rapid spread of SARS-CoV-2 is endangering global health and the economy, the development of strategies to contain the virus's spread are urgently needed. At present, various diagnostic kits to test for SARS-CoV-2 are available for use to initiate appropriate treatment faster and to limit further spread of the virus. Several drugs have demonstrated in vitro activity against SARS-CoV-2 or potential clinical benefits. In addition, institutions and companies worldwide are working tirelessly to develop treatments and vaccines against COVID-19. However, no drug or vaccine has yet been specifically approved for COVID-19. Given the urgency of the outbreak, we focus here on recent advances in the diagnostics, treatment, and vaccine development for SARS-CoV-2 infection, helping to guide strategies to address the current COVID-19 pandemic.