The Long-Term Safety, Public Health Impact, and Cost-Effectiveness of Routine Vaccination with a Recombinant, Live-Attenuated Dengue Vaccine (Dengvaxia): A Model Comparison Study

Effect of single-dose, live, attenuated dengue vaccine in children with or without previous dengue on risk of subsequent, virologically confirmed dengue in Cebu, the Philippines: a longitudinal, prospective, population-based cohort study

BACKGROUND

A three-dose dengue vaccine (CYD-TDV) was licensed for use in children aged 9 years and older starting in 2015 in several dengue-endemic countries. In 2016, the Philippine Department of Health implemented a dengue vaccination programme, which was discontinued because of safety concerns. We assessed the relative risk of developing virologically confirmed dengue among children who did or did not receive a single dose of CYD-TDV by previous dengue virus (DENV) infections at baseline classified as none, one, and two or more infections.

METHODS

In this longitudinal, prospective, population-based cohort study, we enrolled healthy children (aged 9-14 years) residing in Bogo or Balamban, Cebu, Philippines, between May 2, and June 2, 2017, before a mass dengue vaccination campaign, via the Rural Health Unit in Bogo and three Rural Health Units in Balamban. We collected demographic information and sera for baseline DENV serostatus and conducted active surveillance for acute febrile illness. Children who developed acute febrile illness were identified, clinical data were collected, and blood was drawn for confirmation of dengue by RT-PCR. The primary outcome was the relative risk of developing virologically confirmed dengue among children who received or did not receive a single dose of CYD-TDV by DENV serostatus at baseline.

FINDINGS

A single dose of CYD-TDV did not confer protection against virologically confirmed dengue in children who had none or one previous DENV infection at baseline. One dose conferred significant protection against hospital admission for virologically confirmed dengue among participants who had two or more previous DENV infections at baseline during the first 3 years (70%, 95% CI 20-88; p=0·017) and the entire follow-up period (67%, 19-87; p=0·016).

INTERPRETATION

The risk of developing virologically confirmed dengue after a single dose of CYD-TDV varied by baseline DENV serostatus. Since the study assessed the effect of only a single dose, the findings cannot inform decisions on vaccination by public health officers. However, the findings have implications for children who receive an incomplete vaccination regimen and these results should prompt more detailed analyses in future trials on dengue vaccines.

FUNDING

The Philippine Department of Health, Hanako Foundation, WHO, Swedish International Development Cooperation Agency, International Vaccine Institute, University of North Carolina, and US National Institute of Allergy and Infectious Diseases.

In vitro enhancement of Zika virus infection by preexisting West Nile virus antibodies in human plasma-derived immunoglobulins revealed after P2 binding site-specific enrichment

Human immunoglobulin preparations contain a diverse range of polyclonal antibodies that reflect past immune responses against pathogens encountered by the blood donor population. In this study, we examined a panel of intravenous immunoglobulins (IGIVs) manufactured over the past two decades (1998-2020) for their capacity to neutralize or enhance Zika virus (ZIKV) infection in vitro. These IGIVs were selected specifically based on their production dates in relation to the occurrences of two flavivirus outbreaks in the U.S.: the West Nile virus (WNV) outbreak in 1999 and the ZIKV outbreak in 2015. As demonstrated by enzyme-linked immunosorbent assay (ELISA) experiments, IGIVs made before the ZIKV outbreak already harbored antibodies that bind to various peptides across the envelope protein of ZIKV because of the WNV outbreak. Using phage display, the most dominant binding site was mapped precisely to the P2 peptide between residues 211 and 230 within domain II, where BF1176-56, an anti-ZIKV monoclonal antibody, also binds. When tested in permissive Vero E6 cells for ZIKV neutralization, the IGIVs, even after undergoing rigorous enrichment for P2 binding specificity, failed, as did BF1176-56. Meanwhile, BF1176-56 enhanced ZIKV infection in both FcγRII-expressing K562 cells and human peripheral blood mononuclear cells. However, for enhancement by the IGIVs to be detected in these cells, a substantial increase in their P2 binding specificity was required, thus linking the P2 site with ZIKV enhancement in vitro. Our findings warrant further study of the significance of elevated levels of anti-WNV antibodies in IGIVs, considering that various mechanisms operating in vivo may modulate ZIKV infection outcomes.IMPORTANCEWe investigated the capacity of intravenous immunoglobulins manufactured previously over two decades (1998-2020) to neutralize or enhance Zika virus infection in vitro. West Nile virus antibodies in IGIVs could not neutralize Zika virus initially; however, once the IGIVs were concentrated further, they enhanced its infection. These findings lay the groundwork for exploring how preexisting WNV antibodies in IGIVs could impact Zika infection, both in vitro and in vivo. Our observations are historically significant, since we tested a panel of IGIV lots that were carefully selected based on their production dates which covered two major flavivirus outbreaks in the U.S.: the WNV outbreak in 1999 and the ZIKV outbreak in 2015. These findings will facilitate our understanding of the interplay among closely related viral pathogens, particularly from a historical perspective regarding large blood donor populations. They should remain relevant for future outbreaks of emerging flaviviruses that may potentially affect vulnerable populations.

Scenario design for infectious disease projections: Integrating concepts from decision analysis and experimental design

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, situational awareness, horizon scanning, forecasting, and value of information) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings.

When do we need multiple infectious disease models? Agreement between projection rank and magnitude in a multi-model setting

Mathematical models are useful for public health planning and response to infectious disease threats. However, different models can provide differing results, which can hamper decision making if not synthesized appropriately. To address this challenge, multi-model hubs convene independent modeling groups to generate ensembles, known to provide more accurate predictions of future outcomes. Yet, these hubs are resource intensive, and how many models are sufficient in a hub is not known. Here, we compare the benefit of predictions from multiple models in different contexts: (1) decision settings that depend on predictions of quantitative outcomes (e.g., hospital capacity planning), where assessments of the benefits of multi-model ensembles have largely focused; and (2) decisions settings that require the ranking of alternative epidemic scenarios (e.g., comparing outcomes under multiple possible interventions and biological uncertainties). We develop a mathematical framework to mimic a multi-model prediction setting, and use this framework to quantify how frequently predictions from different models agree. We further explore multi-model agreement using real-world, empirical data from 14 rounds of U.S. COVID-19 Scenario Modeling Hub projections. Our results suggest that the value of multiple models could be different in different decision contexts, and if only a few models are available, focusing on the rank of alternative epidemic scenarios could be more robust than focusing on quantitative outcomes. Although additional exploration of the sufficient number of models for different contexts is still needed, our results indicate that it may be possible to identify decision contexts where it is robust to rely on fewer models, a finding that can inform the use of modeling resources during future public health crises.

Dengue virus exploits autophagy vesicles and secretory pathways to promote transmission by human dendritic cells

Dengue virus (DENV), transmitted by infected mosquitoes, is a major public health concern, with approximately half the world's population at risk for infection. Recent decades have increasing incidence of dengue-associated disease alongside growing frequency of outbreaks. Although promising progress has been made in anti-DENV immunizations, post-infection treatment remains limited to non-specific supportive treatments. Development of antiviral therapeutics is thus required to limit DENV dissemination in humans and to help control the severity of outbreaks. Dendritic cells (DCs) are amongst the first cells to encounter DENV upon injection into the human skin mucosa, and thereafter promote systemic viral dissemination to additional human target cells. Autophagy is a vesicle trafficking pathway involving the formation of cytosolic autophagosomes, and recent reports have highlighted the extensive manipulation of autophagy by flaviviruses, including DENV, for viral replication. However, the temporal profiling and function of autophagy activity in DENV infection and transmission by human primary DCs remains poorly understood. Herein, we demonstrate that mechanisms of autophagosome formation and extracellular vesicle (EV) release have a pro-viral role in DC-mediated DENV transmission. We show that DENV exploits early-stage canonical autophagy to establish infection in primary human DCs. DENV replication enhanced autophagosome formation in primary human DCs, and intrinsically-heightened autophagosome biogenesis correlated with relatively higher rates of DC susceptibility to DENV. Furthermore, our data suggest that viral replication intermediates co-localize with autophagosomes, while productive DENV infection introduces a block at the late degradative stages of autophagy in infected DCs but not in uninfected bystander cells. Notably, we identify for the first time that approximately one-fourth of DC-derived CD9/CD81/CD63+ EVs co-express canonical autophagy marker LC3, and demonstrate that DC-derived EV populations are an alternative, cell-free mechanism by which DCs promote DENV transmission to additional target sites. Taken together, our study highlights intersections between autophagy and secretory pathways during viral infection, and puts forward autophagosome accumulation and viral RNA-laden EVs as host determinants of DC-mediated DENV infection in humans. Host-directed therapeutics targeting autophagy and exocytosis pathways thus have potential to enhance DC-driven resistance to DENV acquisition and thereby limit viral dissemination by initial human target cells following mosquito-to-human transmission of DENV.

Informing Public Health Policies with Models for Disease Burden, Impact Evaluation, and Economic Evaluation

Conducting real-world public health experiments is often costly, time-consuming, and ethically challenging, so mathematical models have a long-standing history of being used to inform policy. Applications include estimating disease burden, performing economic evaluation of interventions, and responding to health emergencies such as pandemics. Models played a pivotal role during the COVID-19 pandemic, providing early detection of SARS-CoV-2's pandemic potential and informing subsequent public health measures. While models offer valuable policy insights, they often carry limitations, especially when they depend on assumptions and incomplete data. Striking a balance between accuracy and timely decision-making in rapidly evolving situations such as disease outbreaks is challenging. Modelers need to explore the extent to which their models deviate from representing the real world. The uncertainties inherent in models must be effectively communicated to policy makers and the public. As the field becomes increasingly influential, it needs to develop reporting standards that enable rigorous external scrutiny.

Spatial analysis of dengue transmission in an endemic city in Brazil reveals high spatial structuring on local dengue transmission dynamics

In the last decades, dengue has become one of the most widespread mosquito-borne arboviruses in the world, with an increasing incidence in tropical and temperate regions. The mosquito Aedes aegypti is the dengue primary vector and is more abundant in highly urbanized areas. Traditional vector control methods have showing limited efficacy in sustaining mosquito population at low levels to prevent dengue virus outbreaks. Considering disease transmission is not evenly distributed in the territory, one perspective to enhance vector control efficacy relies on identifying the areas that concentrate arbovirus transmission within an endemic city, i.e., the hotspots. Herein, we used a 13-month timescale during the SARS-Cov-2 pandemic and its forced reduction in human mobility and social isolation to investigate the spatiotemporal association between dengue transmission in children and entomological indexes based on adult Ae. aegypti trapping. Dengue cases and the indexes Trap Positive Index (TPI) and Adult Density Index (ADI) varied seasonally, as expected: more than 51% of cases were notified on the first 2 months of the study, and higher infestation was observed in warmer months. The Moran's Eigenvector Maps (MEM) and Generalized Linear Models (GLM) revealed a strong large-scale spatial structuring in the positive dengue cases, with an unexpected negative correlation between dengue transmission and ADI. Overall, the global model and the purely spatial model presented a better fit to data. Our results show high spatial structure and low correlation between entomological and epidemiological data in Foz do Iguaçu dengue transmission dynamics, suggesting the role of human mobility might be overestimated and that other factors not evaluated herein could be playing a significant role in governing dengue transmission.

Shifting patterns of dengue three years after Zika virus emergence in Brazil

In 2015, the Zika virus (ZIKV) emerged in Brazil, leading to widespread outbreaks in Latin America. Following this, many countries in these regions reported a significant drop in the circulation of dengue virus (DENV), which resurged in 2018-2019. We examine age-specific incidence data to investigate changes in DENV epidemiology before and after the emergence of ZIKV. We observe that incidence of DENV was concentrated in younger individuals during resurgence compared to 2013-2015. This trend was more pronounced in Brazilian states that had experienced larger ZIKV outbreaks. Using a mathematical model, we show that ZIKV-induced cross-protection alone, often invoked to explain DENV decline across Latin America, cannot explain the observed age-shift without also assuming some form of disease enhancement. Our results suggest that a sudden accumulation of population-level immunity to ZIKV could suppress DENV and reduce the mean age of DENV incidence via both protective and disease-enhancing interactions.

Global risk of selection and spread of Plasmodium falciparum histidine-rich protein 2 and 3 gene deletions

In the thirteen years since the first report of pfhrp2-deleted parasites in 2010, the World Health Organization (WHO) has found that 40 of 47 countries surveyed worldwide have reported pfhrp2/3 gene deletions. Due to a high prevalence of pfhrp2/3 deletions causing false-negative HRP2 RDTs, in the last five years, Eritrea, Djibouti and Ethiopia have switched or started switching to using alternative RDTs, that target pan-specific-pLDH or P. falciparum specific-pLDH alone of in combination with HRP2. However, manufacturing of alternative RDTs has not been brought to scale and there are no WHO prequalified combination tests that use Pf-pLDH instead of HRP2 for P. falciparum detection. For these reasons, the continued spread of pfhrp2/3 deletions represents a growing public health crisis that threatens efforts to control and eliminate P. falciparum malaria. National malaria control programmes, their implementing partners and test developers desperately seek pfhrp2/3 deletion data that can inform their immediate and future resource allocation. In response, we use a mathematical modelling approach to evaluate the global risk posed by pfhrp2/3 deletions and explore scenarios for how deletions will continue to spread in Africa. We incorporate current best estimates of the prevalence of pfhrp2/3 deletions and conduct a literature review to estimate model parameters known to impact the selection of pfhrp2/3 deletions for each malaria endemic country. We identify 20 countries worldwide to prioritise for surveillance and future deployment of alternative RDT, based on quickly selecting for pfhrp2/3 deletions once established. In scenarios designed to explore the continued spread of deletions in Africa, we identify 10 high threat countries that are most at risk of deletions both spreading to and subsequently being rapidly selected for. If HRP2-based RDTs continue to be relied on for malaria case management, we predict that the major route for pfhrp2 deletions to spread is south out from the current hotspot in the Horn of Africa, moving through East Africa over the next 20 years. We explore the variation in modelled timelines through an extensive parameter sensitivity analysis and despite wide uncertainties, we identify three countries that have not yet switched RDTs (Senegal, Zambia and Kenya) that are robustly identified as high risk for pfhrp2/3 deletions. These results provide a refined and updated prediction model for the emergence of pfhrp2/3 deletions in an effort to help guide pfhrp2/3 policy and prioritise future surveillance efforts and innovation.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, value of information, situational awareness, horizon scanning, and forecasting) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings.

The potential global cost-effectiveness of prospective Strep A vaccines and associated implementation efforts

Group A Streptococcus causes a wide range of diseases from relatively mild infections including pharyngitis to more severe illnesses such as invasive diseases and rheumatic heart disease (RHD). Our aim is to estimate the cost-effectiveness of a hypothetical Strep A vaccine on multiple disease manifestations at the global-level. Cost-effectiveness analyses were carried out by building on the potential epidemiological impact of vaccines that align with the WHO's Preferred Product Characteristics for Strep A vaccines. Maximum vaccination costs for a cost-effective vaccination strategy were estimated at the thresholds of 1XGDP per capita and health opportunity costs. The maximum cost per fully vaccinated person for Strep A vaccination to be cost-effective was $385-$489 in high-income countries, $213-$312 in upper-income-income countries, $74-$132 in lower-middle-income countries, and $37-$69 in low-income countries for routine vaccination at birth and 5 years of age respectively. While the threshold costs are sensitive to vaccine characteristics such as efficacy, and waning immunity, a cost-effective Strep A vaccine will lower morbidity and mortality burden in all income settings.

Previous Dengue Infection among Children in Puerto Rico and Implications for Dengue Vaccine Implementation

Limited dengue virus (DENV) seroprevalence estimates are available for Puerto Rico, which are needed to inform the potential use and cost-effectiveness of DENV vaccines. The Communities Organized to Prevent Arboviruses (COPA) is a cohort study initiated in 2018 in Ponce, Puerto Rico, to assess arboviral disease risk and provide a platform to evaluate interventions. We recruited participants from households in 38 study clusters, who were interviewed and provided a serum specimen. Specimens from 713 children aged 1 to 16 years during the first year of COPA were tested for the four DENV serotypes and ZIKV using a focus reduction neutralization assay. We assessed the seroprevalence of DENV and ZIKV by age and developed a catalytic model from seroprevalence and dengue surveillance data to estimate the force of infection for DENV during 2003-2018. Overall, 37% (n = 267) were seropositive for DENV; seroprevalence was 9% (11/128) among children aged 1 to 8 years and 44% (256/585) among children aged 9 to 16 years, exceeding the threshold over which DENV vaccination is deemed cost-effective. A total of 33% were seropositive for ZIKV, including 15% among children aged 0 to 8 years and 37% among children aged 9 to 16 years. The highest force of infection occurred in 2007, 2010, and 2012-2013, with low levels of transmission from 2016 to 2018. A higher proportion of children had evidence of multitypic DENV infection than expected, suggesting high heterogeneity in DENV risk in this setting.

Insights into dengue immunity from vaccine trials

The quest for an effective dengue vaccine has culminated in two approved vaccines and another that has completed phase 3 clinical trials. However, shortcomings exist in each, suggesting that the knowledge on dengue immunity used to develop these vaccines was incomplete. Vaccine trial findings could refine our understanding of dengue immunity, because these are experimentally derived, placebo-controlled data. Results from these trials suggest that neutralizing antibody titers alone are insufficient to inform protection against symptomatic infection, implicating a role for cellular immunity in protection. These findings have relevance for both future dengue vaccine development and application of current vaccines for maximal public health benefit.

Cost-effectiveness of sub-national geographically targeted vaccination programs: A systematic review

Immunization is an essential component of national health plans. However, the growing number of new vaccine introductions, vaccination campaigns and increasing administrative costs create logistic and financial challenges, especially in resource-limited settings. Sub-national geographic targeting of vaccination programs is a potential strategy for governments to reduce the impact of infectious disease outbreaks while optimizing resource allocation and reducing costs, promoting sustainability of critically important national immunization plans. We conducted a systematic review of peer-reviewed literature to identify studies that investigated the cost-effectiveness of geographically targeted sub-national vaccination programs, either through routine immunization or supplementary immunization activities. A total of 16 studies were included in our review, covering nine diseases of interest: cholera, dengue, enterotoxigenic Escherichia coli (ETEC), hepatitis A, Japanese encephalitis, measles, rotavirus, Shigella and typhoid fever. All studies modelled cost-effectiveness of geographically targeted vaccination. Despite the variation in study design, disease focus and country context, studies generally found that in countries where a heterogenous burden of disease exists, sub-national geographic targeting of vaccination programs in areas of high disease burden was more cost-effective than a non-targeted strategy. Sensitivity analysis revealed that cost-effectiveness was most sensitive to variations in vaccine price, vaccine efficacy, mortality rate, administrative and operational costs, discount rate, and treatment costs. This systematic review identified several key characteristics related to geographic targeting of vaccination, including the vaccination strategy used, variations in modelling parameters and their impact on cost-effectiveness. Additional research and guidance is needed to support the appropriateness and feasibility of geographically targeted vaccination and to determine what country context would make this a viable complement to routine immunization programs.

A phylogenetic study of dengue virus in urban Vietnam shows long-term persistence of endemic strains

Dengue virus (DENV) causes repeated outbreaks of disease in endemic areas, with patterns of local transmission strongly influenced by seasonality, importation via human movement, immunity, and vector control efforts. An understanding of how each of these interacts to enable endemic transmission (continual circulation of local virus strains) is largely unknown. There are times of the year when no cases are reported, often for extended periods of time, perhaps wrongly implying the successful eradication of a local strain from that area. Individuals who presented at a clinic or hospital in four communes in Nha Trang, Vietnam, were initially tested for DENV antigen presence. Enrolled positive individuals then had their corresponding household members invited to participate, and those who enrolled were tested for DENV. The presence of viral nucleic acid in all samples was confirmed using quantitative polymerase chain reaction, and positive samples were then whole-genome sequenced using an amplicon and target enrichment library preparation techniques and Illumina MiSeq sequencing technology. Generated consensus genome sequences were then analysed using phylogenetic tree reconstruction to categorise sequences into clades with a common ancestor, enabling investigations of both viral clade persistence and introductions. Hypothetical introduction dates were additionally assessed using a molecular clock model that calculated the time to the most recent common ancestor (TMRCA). We obtained 511 DENV whole-genome sequences covering four serotypes and more than ten distinct viral clades. For five of these clades, we had sufficient data to show that the same viral lineage persisted for at least several months. We noted that some clades persisted longer than others during the sampling time, and by comparison with other published sequences from elsewhere in Vietnam and around the world, we saw that at least two different viral lineages were introduced into the population during the study period (April 2017-2019). Next, by inferring the TMRCA from the construction of molecular clock phylogenies, we predicted that two of the viral lineages had been present in the study population for over a decade. We observed five viral lineages co-circulating in Nha Trang from three DENV serotypes, with two likely to have remained as uninterrupted transmission chains for a decade. This suggests clade cryptic persistence in the area, even during periods of low reported incidence.

Spatial repellents: The current roadmap to global recommendation of spatial repellents for public health use

Spatial repellent (SR) products are envisioned to complement existing vector control methods through the continual release of volatile active ingredients (AI) providing: (i) protection against day-time and early-evening biting; (ii) protection in enclosed/semi-enclosed and peri-domestic spaces; (iii) various formulations to fit context-specific applications; and (iv) increased coverage over traditional control methods. SR product AIs also have demonstrated effect against insecticide-resistant vectors linked to malaria and Aedes-borne virus (ABV) transmission. Over the past two decades, key stakeholders, including World Health Organization (WHO) representatives, have met to discuss the role of SRs in reducing arthropod-borne diseases based on existing evidence. A key focus has been to establish a critical development path for SRs, including scientific, regulatory and social parameters that would constitute an outline for a SR target product profile, i.e. optimum product characteristics. The principal gap is the lack of epidemiological data demonstrating SR public health impact across a range of different ecological and epidemiological settings, to inform a WHO policy recommendation. Here we describe in brief trials that are designed to fulfill evidence needs for WHO assessment and initial projections of SR cost-effectiveness against malaria and dengue.

Interactions between seasonal temperature variation and temporal synchrony drive increased arbovirus co-infection incidence

Though instances of arthropod-borne (arbo)virus co-infection have been documented clinically, the overall incidence of arbovirus co-infection and its drivers are not well understood. Now that dengue, Zika and chikungunya viruses are all in circulation across tropical and subtropical regions of the Americas, it is important to understand the environmental and biological conditions that make co-infections more likely to occur. To understand this, we developed a mathematical model of co-circulation of two arboviruses, with transmission parameters approximating dengue, Zika and/or chikungunya viruses, and co-infection possible in both humans and mosquitoes. We examined the influence of seasonal timing of arbovirus co-circulation on the extent of co-infection. By undertaking a sensitivity analysis of this model, we examined how biological factors interact with seasonality to determine arbovirus co-infection transmission and prevalence. We found that temporal synchrony of the co-infecting viruses and average temperature were the most influential drivers of co-infection incidence. Our model highlights the synergistic effect of co-transmission from mosquitoes, which leads to more than double the number of co-infections than would be expected in a scenario without co-transmission. Our results suggest that appreciable numbers of co-infections are unlikely to occur except in tropical climates when the viruses co-occur in time and space.

Dengue vaccine development: challenges and prospects

PURPOSE OF REVIEW

Dengue vaccine development is a high public health priority. To date, no dengue vaccine is in widespread use. Here we review the challenges in dengue development and the latest results for the second-generation dengue vaccines.

RECENT FINDINGS

The biggest hurdle is the immunological interaction between the four antigenically distinct dengue serotypes. The advantages of second-generation dengue vaccines are the inclusion of nonstructural proteins of the dengue backbone and a more convenient dosing with reduced numbers of doses needed.

SUMMARY

Although dengue-primed individuals can already benefit from vaccination with the first licensed dengue vaccine CYD-TDV, the public health need for the dengue-naive population has not yet been met. The urgent need remains to identify correlates of both protection and enhancement; until such correlates have been identified, all second-generation dengue vaccines still need to go through full phase 3 trials. The 5-year efficacy and safety data for both second-generation dengue vaccines are imminent.

"To do, or not to do?": determinants of stakeholders' acceptance on dengue vaccine using PLS-SEM analysis in Malaysia

Background

Dengue vaccine is a promising alternative for protecting communities from dengue. Nevertheless, public acceptance of the dengue vaccine must be considered before the authorities decide to carry out intensified research and recommend the vaccine adoption. This study aimed to assess the stakeholders' acceptability of the dengue vaccine and determine the factors that influence their intentions to adopt it.

Methods

Survey data collected from 399 respondents who represented two primary stakeholder groups: scientist (n = 202) and public (n = 197), were analysed using the partial least squares-structural equation modelling (PLS-SEM) technique.

Results

The findings revealed that the stakeholders claimed to have a highly positive attitude and intention to adopt the vaccine, perceived the vaccine as having high benefits, and displayed a high degree of religiosity and trust in the key players. The results also demonstrated that attitude and perceived benefits significantly influenced the intention to adopt the dengue vaccine. Furthermore, the perceived benefit was the most significant predictor of attitude to the dengue vaccine, followed by religiosity, attitudes to technology, and trust in key players.

Conclusion

The findings showed that the stakeholders in Malaysia were optimistic about the dengue vaccine with a positive attitude and perceived benefits as significant predictors of intention to adopt the vaccine. Hence, ongoing research can be intensified with the end target of recommending the vaccine for public adoption in hotspot areas. This finding contributes to the consumer behaviour literature while also providing helpful information to the government, policymakers, and public health officials about effective strategies for driving dengue vaccine acceptance in Malaysia and other countries with a history of severe dengue transmission.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13967-3.

Green Nano-Biotechnology: A New Sustainable Paradigm to Control Dengue Infection

Dengue is a growing mosquito-borne viral disease prevalent in 128 countries, while 3.9 billion people are at high risk of acquiring the infection. With no specific treatment available, the only way to mitigate the risk of dengue infection is through controlling of vector, i.e., Aedes aegypti. Nanotechnology-based prevention strategies like biopesticides with nanoformulation are now getting popular for preventing dengue fever. Metal nanoparticles (NPs) synthesized by an eco-friendly process, through extracts of medicinal plants have indicated potential anti-dengue applications. Green synthesis of metal NPs is simple, cost-effective, and devoid of hazardous wastes. The recent progress in the phyto-synthesized multifunctional metal NPs for anti-dengue applications has encouraged us to review the available literature and mechanistic aspects of the dengue control using green-synthesized NPs. Furthermore, the molecular bases of the viral inhibition through NPs and the nontarget impacts or hazards with reference to the environmental integrity are discussed in depth. Till date, major focus has been on green synthesis of silver and gold NPs, which need further extension to other innovative composite nanomaterials. Further detailed mechanistic studies are required to critically evaluate the mechanistic insights during the synthesis of the biogenic NPs. Likewise, detailed analysis of the toxicological aspects of NPs and their long-term impact in the environment should be critically assessed.

Risk factors for infection with chikungunya and Zika viruses in southern Puerto Rico: A community-based cross-sectional seroprevalence survey

Chikungunya virus (CHIKV) caused a large outbreak in Puerto Rico in 2014, followed by a Zika virus (ZIKV) outbreak in 2016. Communities Organized for the Prevention of Arboviruses (COPA) is a cohort study in southern Puerto Rico, initiated in 2018 to measure arboviral disease risk and provide a platform to evaluate interventions. To identify risk factors for infection, we assessed prevalence of previous CHIKV infection and recent ZIKV and DENV infection in a cross-sectional study among COPA participants. Participants aged 1-50 years (y) were recruited from randomly selected households in study clusters. Each participant completed an interview and provided a blood specimen, which was tested by anti-CHIKV IgG ELISA assay and anti-ZIKV and anti-DENV IgM MAC-ELISA assays. We assessed individual, household, and community factors associated with a positive result for CHIKV or ZIKV after adjusting for confounders. During 2018-2019, 4,090 participants were enrolled; 61% were female and median age was 28y (interquartile range [IQR]: 16-41). Among 4,035 participants tested for CHIKV, 1,268 (31.4%) had evidence of previous infection. CHIKV infection prevalence was lower among children 1-10 years old compared to people 11 and older (adjusted odds ratio [aOR] 2.30; 95% CI 1.71-3.08). Lower CHIKV infection prevalence was associated with home screens (aOR 0.51; 95% CI 0.42-0.61) and air conditioning (aOR 0.64; 95% CI 0.54-0.77). CHIKV infection prevalence also varied by study cluster of residence and insurance type. Few participants (16; 0.4%) had evidence of recent DENV infection by IgM. Among 4,035 participants tested for ZIKV, 651 (16%) had evidence of recent infection. Infection prevalence increased with older age, from 7% among 1-10y olds up to 19% among 41-50y olds (aOR 3.23; 95% CI 2.16-4.84). Males had an increased risk of Zika infection prevalence compared with females (aOR 1.31; 95% CI 1.09-1.57). ZIKV infection prevalence also decreased with the presence of home screens (aOR 0.66; 95% CI 0.54-0.82) and air conditioning (aOR 0.69; 95% CI 0.57-0.84). Similar infection patterns were observed for recent ZIKV infection prevalence and previous CHIKV infection prevalence by age, and the presence of screens and air conditioners in the home decreased infection risk from both viruses by as much as 50%.

Dengue: A Growing Problem With New Interventions

Dengue is the disease caused by 1 of 4 distinct, but closely related dengue viruses (DENV-1-4) that are transmitted by Aedes spp. mosquito vectors. It is the most common arboviral disease worldwide, with the greatest burden in tropical and sub-tropical regions. In the absence of effective prevention and control measures, dengue is projected to increase in both disease burden and geographic range. Given its increasing importance as an etiology of fever in the returning traveler or the possibility of local transmission in regions in the United States with competent vectors, as well as the risk for large outbreaks in endemic US territories and associated states, clinicians should understand its clinical presentation and be familiar with appropriate testing, triage, and management of patients with dengue. Control and prevention efforts reached a milestone in June 2021 when the Advisory Committee on Immunization Practices (ACIP) recommended Dengvaxia for routine use in children aged 9 to 16 years living in endemic areas with laboratory confirmation of previous dengue virus infection. Dengvaxia is the first vaccine against dengue to be recommended for use in the United States and one of the first to require laboratory testing of potential recipients to be eligible for vaccination. In this review, we outline dengue pathogenesis, epidemiology, and key clinical features for front-line clinicians evaluating patients presenting with dengue. We also provide a summary of Dengvaxia efficacy, safety, and considerations for use as well as an overview of other potential new tools to control and prevent the growing threat of dengue .

Capeding M, Padilla CD, Sasmono RT, Hafalla JCR, Hibberd ML. Combining rapid diagnostic tests to estimate primary and post-primary dengue immune status at the point of care

BACKGROUND

Characterising dengue virus (DENV) infection history at the point of care is challenging as it relies on intensive laboratory techniques. We investigated how combining different rapid diagnostic tests (RDTs) can be used to accurately determine the primary and post-primary DENV immune status of reporting patients during diagnosis.

METHODS AND FINDINGS

Serum from cross-sectional surveys of acute suspected dengue patients in Indonesia (N:200) and Vietnam (N: 1,217) were assayed using dengue laboratory assays and RDTs. Using logistic regression modelling, we determined the probability of being DENV NS1, IgM and IgG RDT positive according to corresponding laboratory viremia, IgM and IgG ELISA metrics. Laboratory test thresholds for RDT positivity/negativity were calculated using Youden's J index and were utilized to estimate the RDT outcomes in patients from the Philippines, where only data for viremia, IgM and IgG were available (N:28,326). Lastly, the probabilities of being primary or post-primary according to every outcome using all RDTs, by day of fever, were calculated. Combining NS1, IgM and IgG RDTs captured 94.6% (52/55) and 95.4% (104/109) of laboratory-confirmed primary and post-primary DENV cases, respectively, during the first 5 days of fever. Laboratory test predicted, and actual, RDT outcomes had high agreement (79.5% (159/200)). Among patients from the Philippines, different combinations of estimated RDT outcomes were indicative of post-primary and primary immune status. Overall, IgG RDT positive results were confirmatory of post-primary infections. In contrast, IgG RDT negative results were suggestive of both primary and post-primary infections on days 1-2 of fever, yet were confirmatory of primary infections on days 3-5 of fever.

CONCLUSION

We demonstrate how the primary and post-primary DENV immune status of reporting patients can be estimated at the point of care by combining NS1, IgM and IgG RDTs and considering the days since symptoms onset. This framework has the potential to strengthen surveillance operations and dengue prognosis, particularly in low resource settings.

Risk and predictive factors for severe dengue infection: A systematic review and meta-analysis

Background

Dengue is a major public health issue worldwide and severe dengue (SD) is life threatening. It is critical to triage patients with dengue infection in the early stage. However, there is limited knowledge on early indicators of SD. The objective of this study is to identify risk factors for the prognosis of SD and try to find out some potential predictive factors for SD from dengue fever (DF) in the early of infection.

Methods

The PubMed, Cochrane Library and Web of Science databases were searched for relevant studies from June 1999 to December 2020. The pooled odds ratio (OR) or standardized mean difference (SMD) with 95% confidence intervals (CI) of identified factors was calculated using a fixed or random effect model in the meta-analysis. Tests for heterogeneity, publication bias, subgroup analyses, meta-regression, and a sensitivity analysis were further performed.

Findings

A total of 6,848 candidate articles were retrieved, 87 studies with 35,184 DF and 8,173 SD cases met the eligibility criteria. A total of 64 factors were identified, including population and virus characteristics, clinical symptoms and signs, laboratory biomarkers, cytokines, and chemokines; of these factors, 34 were found to be significantly different between DF and SD, while the other 30 factors were not significantly different between the two groups after pooling the data from the relevant studies. Additionally, 9 factors were positive associated with SD within 7 days after illness when the timing subgroup analysis were performed.

Conclusions

Practical factors and biomarkers for the identification of SD were established, which will be helpful for a prompt diagnosis and early effective treatment for those at greatest risk. These outcomes also enhance our knowledge of the clinical manifestations and pathogenesis of SD.

Tetravalent formulation of Polymeric nanoparticle-based vaccine induces a potent immune response against Dengue virus

Dengue is a mosquito-borne disease caused by the four serotypes of dengue virus (DENV 1-4). It is growing at an alarming rate globally, which could be partly attributed to the...

Prevention and control of dengue and Chikungunya in Colombia: A cost-effectiveness analysis

Background

Chikungunya and dengue are emerging diseases that have caused large outbreaks in various regions of the world. Both are both spread by Aedes aegypti and Aedes albopictus mosquitos. We developed a dynamic transmission model of chikungunya and dengue, calibrated to data from Colombia (June 2014 –December 2017).

Methodology/Principal findings

We evaluated the health benefits and cost-effectiveness of residual insecticide treatment, long-lasting insecticide-treated nets, routine dengue vaccination for children aged 9, catchup vaccination for individuals aged 10–19 or 10–29, and portfolios of these interventions. Model calibration resulted in 300 realistic transmission parameters sets that produced close matches to disease-specific incidence and deaths. Insecticide was the preferred intervention and was cost-effective. Insecticide averted an estimated 95 chikungunya cases and 114 dengue cases per 100,000 people, 61 deaths, and 4,523 disability-adjusted life years (DALYs). In sensitivity analysis, strategies that included dengue vaccination were cost-effective only when the vaccine cost was 14% of the current price.

Conclusions/Significance

Insecticide to prevent chikungunya and dengue in Colombia could generate significant health benefits and be cost-effective. Because of limits on diagnostic accuracy and vaccine efficacy, the cost of dengue testing and vaccination must decrease dramatically for such vaccination to be cost-effective in Colombia. The vectors for chikungunya and dengue have recently spread to new regions, highlighting the importance of understanding the effectiveness and cost-effectiveness of policies aimed at preventing these diseases.

Chikungunya and dengue are emerging diseases that have caused large outbreaks in various regions of the world. Both are both spread by Aedes aegypti and Aedes albopictus mosquitos. To evaluate the effectiveness and cost-effectiveness of interventions aimed at controlling either of these diseases, it is important to consider the potential effects on both diseases, as an intervention that reduces the mosquito population will reduce the spread of both diseases. We developed a dynamic transmission model of chikungunya and dengue, calibrated to data from Colombia. We evaluated the health benefits and cost-effectiveness of the following interventions: residual insecticide treatment, long-lasting insecticide-treated nets, routine dengue vaccination for children aged 9, catchup dengue vaccination for individuals aged 10–19 or 10–29, and portfolios of these interventions. In all vaccination scenarios, we considered testing for previous exposure to dengue. We found that insecticide to prevent chikungunya and dengue in Colombia could generate significant health benefits and be cost-effective. While the dengue vaccine was effective in preventing cases and deaths, costs of diagnostic testing and vaccination must decrease for dengue vaccination to be considered cost-effective.

Health economic analyses of secondary vaccine effects: a systematic review and policy insights

INTRODUCTION

: Numerous analyses demonstrate substantial health economic impacts of primary vaccine effects (preventing or mitigating clinical manifestations of the diseases they target), but vaccines may also be associated with secondary effects, previously known as non-specific, heterologous, or off-target effects.

AREAS COVERED

: We define key concepts to distinguish primary and secondary vaccine effects for health economic analyses, summarized terminology used in different fields, and perform a systematic review of health economic analyses focused on secondary vaccine effects (SVEs).

EXPERT OPINION

: Health economists integrate evidence from multiple fields, which often use incomplete or inconsistent definitions. Like regulators and policy makers, health economists require high-quality evidence of specific effects. Consistent with the limited evidence on mechanisms of action for SVEs, the associated health economic literature remains highly limited, with 4 studies identified by our systematic review. The lack of specific and well-controlled evidence that supports quantification of specific SVEs limits the consideration of these effects in vaccine research, development, regulatory, and recommendation decisions and health economic analyses.

Dengue Vaccine: Recommendations of the Advisory Committee on Immunization Practices, United States, 2021

Dengue is a vectorborne infectious disease caused by dengue viruses (DENVs), which are predominantly transmitted by Aedes aegypti and Aedes albopictus mosquitos. Dengue is caused by four closely related viruses (DENV-1–4), and a person can be infected with each serotype for a total of four infections during their lifetime. Areas where dengue is endemic in the United States and its territories and freely associated states include Puerto Rico, American Samoa, the U.S. Virgin Islands, the Federated States of Micronesia, the Republic of Marshall Islands, and the Republic of Palau. This report summarizes the recommendations of the Advisory Committee on Immunization Practices (ACIP) for use of the Dengvaxia vaccine in the United States. The vaccine is a live-attenuated, chimeric tetravalent dengue vaccine built on a yellow fever 17D backbone. Dengvaxia is safe and effective in reducing dengue-related hospitalizations and severe dengue among persons who have had dengue infection in the past. Previous natural infection is important because Dengvaxia is associated with an increased risk for severe dengue in those who experience their first natural infection (i.e., primary infection) after vaccination. Dengvaxia was licensed by the Food and Drug Administration for use among children and adolescents aged 9–16 years (referred to in this report as children). ACIP recommends vaccination with Dengvaxia for children aged 9–16 having evidence of a previous dengue infection and living in areas where dengue is endemic. Evidence of previous dengue infection, such as detection of anti-DENV immunoglobulin G with a highly specific serodiagnostic test, will be required for eligible children before vaccination.

Benefit-Risk Assessment of Vaccines. Part I: A Systematic Review to Identify and Describe Studies About Quantitative Benefit-Risk Models Applied to Vaccines

Introduction

Understanding the balance between the benefits and risks of vaccination is essential to ensure informed and adequate public health decision making. Quantitative benefit–risk models (qBRm) represent useful tools to help decision makers with supporting benefit–risk assessment throughout the lifecycle of a medical product. However, few initiatives have been launched to harmonise qBRm approaches, specifically for vaccines.

Objectives

The aim of this paper was to identify publications about qBRm applied to vaccines through a systematic literature review, and to describe their characteristics.

Methods

Medline, Scopus and Institute for Scientific Information Web of Knowledge databases were searched to identify articles in English, published from database inceptions up to December 2019. The search strategy included the combination of three key concepts: ‘benefit–risk’, ‘modelling’ and ‘vaccines’. Data extracted included the modelling context and the methodological approaches used.

Results

Of 3172 publications screened, 48 original publications were included. Most of the selected studies were published over the past decade and focused on rotavirus (15), dengue (10) and influenza (6) vaccines. The majority (30) of studies reported analyses related to high-income countries. The methodology of the studies differed, particularly in modelling techniques, benefit–risk measures, and sensitivity analyses. The present work also pointed out a high level of variability in the quality of reporting across studies, with particular regard to input parameters and methodological approaches.

Conclusions

This review provides an extensive list of qBRm applied to vaccines. Discrepancies across studies were identified during our review. While the number of published qBRm studies is increasing, no reporting guidance for qBRm applied to vaccines is currently available. This may affect decision makers’ confidence in the results and their benefit–risk assessment(s); therefore, the development of such reporting guidance is highly needed.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00984-7) contains supplementary material, which is available to authorized users.

Pandemic-associated mobility restrictions could cause increases in dengue virus transmission

BACKGROUND

The COVID-19 pandemic has induced unprecedented reductions in human mobility and social contacts throughout the world. Because dengue virus (DENV) transmission is strongly driven by human mobility, behavioral changes associated with the pandemic have been hypothesized to impact dengue incidence. By discouraging human contact, COVID-19 control measures have also disrupted dengue vector control interventions, the most effective of which require entry into homes. We sought to investigate how and why dengue incidence could differ under a lockdown scenario with a proportion of the population sheltered at home.

METHODOLOGY & PRINCIPAL FINDINGS

We used an agent-based model with a realistic treatment of human mobility and vector control. We found that a lockdown in which 70% of the population sheltered at home and which occurred in a season when a new serotype invaded could lead to a small average increase in cumulative DENV infections of up to 10%, depending on the time of year lockdown occurred. Lockdown had a more pronounced effect on the spatial distribution of DENV infections, with higher incidence under lockdown in regions with higher mosquito abundance. Transmission was also more focused in homes following lockdown. The proportion of people infected in their own home rose from 54% under normal conditions to 66% under lockdown, and the household secondary attack rate rose from 0.109 to 0.128, a 17% increase. When we considered that lockdown measures could disrupt regular, city-wide vector control campaigns, the increase in incidence was more pronounced than with lockdown alone, especially if lockdown occurred at the optimal time for vector control.

CONCLUSIONS & SIGNIFICANCE

Our results indicate that an unintended outcome of lockdown measures may be to adversely alter the epidemiology of dengue. This observation has important implications for an improved understanding of dengue epidemiology and effective application of dengue vector control. When coordinating public health responses during a syndemic, it is important to monitor multiple infections and understand that an intervention against one disease may exacerbate another.

Cost-effectiveness of dengue vaccination in Puerto Rico

An effective and widely used vaccine could reduce the burden of dengue virus (DENV) around the world. DENV is endemic in Puerto Rico, where the dengue vaccine CYD-TDV is currently under consideration as a control measure. CYD-TDV has demonstrated efficacy in clinical trials in vaccinees who had prior dengue virus infection. However, in vaccinees who had no prior dengue virus infection, the vaccine had a modestly elevated risk of hospitalization and severe disease. The WHO therefore recommended a strategy of pre-vaccination screening and vaccination of seropositive persons. To estimate the cost-effectiveness and benefits of this intervention (i.e., screening and vaccination of seropositive persons) in Puerto Rico, we simulated 10 years of the intervention in 9-year-olds using an agent-based model. Across the entire population, we found that 5.5% (4.6%-6.3%) of dengue hospitalizations could be averted. However, we also found that 0.057 (0.045-0.073) additional hospitalizations could occur for every 1,000 people in Puerto Rico due to DENV-naïve children who were vaccinated following a false-positive test results for prior exposure. The ratio of the averted hospitalizations among all vaccinees to additional hospitalizations among DENV-naïve vaccinees was estimated to be 19 (13-24). At a base case cost of vaccination of 382 USD, we found an incremental cost-effectiveness ratio of 122,000 USD per QALY gained. Our estimates can provide information for considerations to introduce the CYD-TDV vaccine in Puerto Rico.

Efficacy profile of the CYD-TDV dengue vaccine revealed by Bayesian survival analysis of individual-level phase III data

Background:

Sanofi-Pasteur’s CYD-TDV is the only licensed dengue vaccine. Two phase three trials showed higher efficacy in seropositive than seronegative recipients. Hospital follow-up revealed increased hospitalisation in 2–5- year-old vaccinees, where serostatus and age effects were unresolved.

Methods:

We fit a survival model to individual-level data from both trials, including year 1 of hospital follow-up. We determine efficacy by age, serostatus, serotype and severity, and examine efficacy duration and vaccine action mechanism.

Results:

Our modelling indicates that vaccine-induced immunity is long-lived in seropositive recipients, and therefore that vaccinating seropositives gives higher protection than two natural infections. Long-term increased hospitalisation risk outweighs short-lived immunity in seronegatives. Independently of serostatus, transient immunity increases with age, and is highest against serotype 4. Benefit is higher in seropositives, and risk enhancement is greater in seronegatives, against hospitalised disease than against febrile disease.

Conclusions:

Our results support vaccinating seropositives only. Rapid diagnostic tests would enable viable ‘screen-then-vaccinate’ programs. Since CYD-TDV acts as a silent infection, long-term safety of other vaccine candidates must be closely monitored.

Funding:

Bill & Melinda Gates Foundation, National Institute for Health Research, UK Medical Research Council, Wellcome Trust, Royal Society.

Clinical trial number:

NCT01373281 and NCT01374516.

CYD Tetravalent Dengue Vaccine Performance by Baseline Immune Profile (Monotypic/Multitypic) in Dengue-Seropositive Individuals

Background

The immune profile of dengue-experienced individuals is a determinant of dengue reinfection severity risk. Individuals with a single prior dengue infection (monotypic) are at highest risk for severe disease, while individuals with ≥ 2 prior dengue infections (multitypic) are at lower risk. The tetravalent dengue vaccine (CYD-TDV) has shown efficacy in the prevention of dengue in individuals with prior dengue infection. We estimated efficacy in individuals with monotypic or multitypic immune profiles.

Methods

Participants enrolled in the immunogenicity subsets of 2 randomized placebo-controlled phase 3 studies (CYD14, NCT01373281; CYD15, NCT01374516) were classified as either monotypic or multitypic, based on measured baseline dengue plaque reduction neutralization test. Vaccine efficacy (VE) against symptomatic virologically confirmed dengue (VCD) was assessed over 25 months and against VCD hospitalization over 6 years.

Results

Of 3927 participants in the immunogenicity subsets, 496 and 257 in the CYD-TDV and placebo groups, respectively, were classified as monotypic immune, and 1227 and 612, respectively, as multitypic immune. VE against symptomatic VCD was 77.4% (95% CI, 56.4%–88.2%) for monotypic and 89.2% (95% CI, 71.5%–95.9%) for multitypic profiles, with corresponding absolute risk reductions (ARRs) of 4.48% (95% CI, 2.32%–6.65%) for monotypics and 1.67% (95% CI, .89%–2.46%) for multitypics. VE against hospitalized VCD was 75.3% (95% CI, 42.7%–90.2%) in monotypics and 81.2% (95% CI, 21.7%–96.8%) in multitypics, with ARRs of 0.95% (95% CI, .37%–1.53%) for monotypics and 0.18% (95% CI, .02%–.34%) for multitypics.

Conclusions

CYD-TDV benefits individuals with monotypic and multitypic immune profiles. Larger public health benefit is expected to derive from the protection of individuals with a monotypic immune profile.

Using Wolbachia to Eliminate Dengue: Will the Virus Fight Back?

Recent field trials have demonstrated that dengue incidence can be substantially reduced by introgressing strains of the endosymbiotic bacterium Wolbachia into Aedes aegypti mosquito populations. This strategy relies on Wolbachia reducing the susceptibility of Ae. aegypti to disseminated infection by positive-sense RNA viruses like dengue. However, RNA viruses are well known to adapt to antiviral pressures. Here, we review the viral infection stages where selection for Wolbachia-resistant virus variants could occur. We also consider the genetic constraints imposed on viruses that alternate between vertebrate and invertebrate hosts, and the likely selection pressures to which dengue virus might adapt in order to be effectively transmitted by Ae. aegypti that carry Wolbachia. While there are hurdles to dengue viruses developing resistance to Wolbachia, we suggest that long-term surveillance for resistant viruses should be an integral component of Wolbachia-introgression biocontrol programs.

Phage display demonstrates durable differences in serological profile by route of inoculation in primary infections of non-human primates with Dengue Virus 1

Natural dengue virus (DENV) infections occur by mosquito bite but how the inoculation route affects the humoral immune response is unknown. We serologically profiled 20 non-human primates (NHP) from a prior study of DENV1 infection where animals were inoculated by mosquito (N = 10) or subcutaneous injection (N = 10). Using a comprehensive, densely tiled and highly redundant pan-flavivirus programmable phage library containing 91,562 overlapping 62 amino acid peptides, we produced a high-resolution map of linear peptide sequences enriched during DENV seroconversion. Profiles in mosquito-inoculated and subcutaneously-inoculated animals were similar up to 90 days after primary infection, but diverged at 1 year with differences in sero-reactivity in the Envelope (E; residues 215–406; p < 0.08), and Nonstructural-3 (NS3; residues 549–615; p < 0.05) proteins in mosquito-inoculated versus subcutaneously-inoculated animals. Within the E protein, residues 339–384 in domain III accounted for > 99% of the observed sero-reactivity difference. Antibody breadth did not vary by mode of inoculation. The differential reactivity to E domain III seen by phage display validated orthogonally by ELISA, but did not correlate with late neutralization titers. Serological profiling of humoral immune responses to DENV infection in NHP by programmable phage display demonstrated durable differences in sero-reactivity by route of inoculation.

Dengue fever and dengue virus in the People's Republic of China

Infection with dengue virus (DENV) leads to symptoms variable from dengue fever to severe dengue, which has posed a huge socioeconomic and disease burden to the world population, particularly in tropical and subtropical regions. To date, four serotypes of DENV (DENV-1 to DENV-4) have been identified to sustain the transmission cycle in humans. In the past decades, dengue incidences have become more frequent, and four serotypes and various genotypes have been identified in PR China. Several large-scale dengue outbreaks and frequent local endemics occurred in the southern and coastal provinces, and the imported dengue cases accounted primarily for the initiation of the epidemics. No antiviral drug exists for dengue, and no vaccine has been approved to use in PR China, however strategies including public awareness, national reporting system of infectious diseases and public health emergencies, vector mosquito control, personal protection, and improved environmental sanitation have greatly reduced dengue prevalence. Some new technologies in vector mosquito control are emerging and being applied for dengue control. China's territory spans tropical, subtropical, and temperate climates, hence understanding the dengue status in China will be of beneficial for the global prevention and control of dengue. Here, we review the dengue status in PR China for the past decades and the strategies emerging for dengue control.

Boosting can explain patterns of fluctuations of ratios of inapparent to symptomatic dengue virus infections

Dengue is the most prevalent arboviral disease worldwide, and the four dengue virus (DENV) serotypes circulate endemically in many tropical and subtropical regions. Numerous studies have shown that the majority of DENV infections are inapparent, and that the ratio of inapparent to symptomatic infections (I/S) fluctuates substantially year-to-year. For example, in the ongoing Pediatric Dengue Cohort Study (PDCS) in Nicaragua, which was established in 2004, the I/S ratio has varied from 16.5:1 in 2006-2007 to 1.2:1 in 2009-2010. However, the mechanisms explaining these large fluctuations are not well understood. We hypothesized that in dengue-endemic areas, frequent boosting (i.e., exposures to DENV that do not lead to extensive viremia and result in a less than fourfold rise in antibody titers) of the immune response can be protective against symptomatic disease, and this can explain fluctuating I/S ratios. We formulate mechanistic epidemiologic models to examine the epidemiologic effects of protective homologous and heterologous boosting of the antibody response in preventing subsequent symptomatic DENV infection. We show that models that include frequent boosts that protect against symptomatic disease can recover the fluctuations in the I/S ratio that we observe, whereas a classic model without boosting cannot. Furthermore, we show that a boosting model can recover the inverse relationship between the number of symptomatic cases and the I/S ratio observed in the PDCS. These results highlight the importance of robust dengue control efforts, as intermediate dengue control may have the potential to decrease the protective effects of boosting.

Pneumococcal Competition Modulates Antibiotic Resistance in the Pre-Vaccination Era: A Modelling Study

The ongoing emergence of antibiotic resistant strains and high frequencies of antibiotic resistance of Streptococcus pneumoniae poses a major public health challenge. How and which ecological and evolutionary mechanisms maintain the coexistence of antibiotic resistant and susceptible strains remains largely an open question. We developed an individual-based, stochastic model expanding on a previous pneumococci modelling framework. We explore how between- and within-host mechanisms of competition can sustain observed levels of resistance to antibiotics in the pre-vaccination era. Our framework considers that within-host competition for co-colonization between resistant and susceptible strains can arise via pre-existing immunity (immunological competition) or intrinsic fitness differences due to resistance costs (ecological competition). We find that beyond stochasticity, population structure or movement, competition at the within-host level can explain observed resistance frequencies. We compare our simulation results to pneumococcal antibiotic resistance data in the European region using approximate Bayesian computation. Our results demonstrate that ecological competition for co-colonization can explain the variation in co-existence of resistant and susceptible pneumococci observed in the pre-vaccination era. Furthermore, we show that within-host pneumococcal competition can facilitate the maintenance of resistance in the pre-vaccination era. Accounting for these competition-related components of pneumococcal dynamics can improve our understanding of drivers for the emergence and maintenance of antibiotic resistance in pneumococci.

On the Use of Markov Models in Pharmacoeconomics: Pros and Cons and Implications for Policy Makers

We present an overview of the main methodological features and the goals of pharmacoeconomic models that are classified in three major categories: regression models, decision trees, and Markov models. In particular, we focus on Markov models and define a semi-Markov model on the cost utility of a vaccine for Dengue fever discussing the key components of the model and the interpretation of its results. Next, we identify some criticalities of the decision rule arising from a possible incorrect interpretation of the model outcomes. Specifically, we focus on the difference between median and mean ICER and on handling the willingness-to-pay thresholds. We also show that the life span of the model and an incorrect hypothesis specification can lead to very different outcomes. Finally, we analyse the limit of Markov model when a large number of states is considered and focus on the implementation of tools that can bypass the lack of memory condition of Markov models. We conclude that decision makers should interpret the results of these models with extreme caution before deciding to fund any health care policy and give some recommendations about the appropriate use of these models.

COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

The economic impact and cost-effectiveness of combined vector-control and dengue vaccination strategies in Thailand: results from a dynamic transmission model

BACKGROUND AND AIMS

Dengue fever is a major public health problem in tropical/subtropical regions. Prior economic analyses have predominantly evaluated either vaccination or vector-control programmes in isolation and do not really consider the incremental benefits and cost-effectiveness of mixed strategies and combination control. We estimated the cost-effectiveness of single and combined approaches in Thailand.

METHODS

The impacts of different control interventions were analysed using a previously published mathematical model of dengue epidemiology and control incorporating seasonality, age structure, consecutive infection, cross protection, immune enhancement and combined vector-host transmission. An economic model was applied to simulation results to estimate the cost-effectiveness of 4 interventions and their various combinations (6 strategies): i) routine vaccination of 1-year olds; ii) chemical vector control strategies targeting adult and larval stages separately; iii) environmental management/ public health education and awareness [EM/ PHEA]). Payer and societal perspectives were considered. The health burden of dengue fever was assessed using disability-adjusted life-years (DALYs) lost. Costs and effects were assessed for 10 years. Costs were discounted at 3% annually and updated to 2013 United States Dollars. Incremental cost-effectiveness analysis was carried out after strategies were rank-ordered by cost, with results presented in a table of incremental analysis. Sensitivity and scenario analyses were undertaken; and the impact and cost-effectiveness of Wolbachia was evaluated in exploratory scenario analyses.

RESULTS

From the payer and societal perspectives, 2 combination strategies were considered optimal, as all other control strategies were dominated. Vaccination plus adulticide plus EM/ PHEA was deemed cost-effective according to multiple cost-effectiveness criteria. From the societal perspective, incremental differences vs. adulticide and EM/ PHEA resulted in costs of $157.6 million and DALYs lost of 12,599, giving an expected ICER of $12,508 per DALY averted. Exploratory scenario analyses showed Wolbachia to be highly cost-effective ($343 per DALY averted) vs. other single control measures.

CONCLUSIONS

Our model shows that individual interventions can be cost-effective, but that important epidemiological reductions and economic impacts are demonstrated when interventions are combined as part of an integrated approach to combating dengue fever. Exploratory scenario analyses demonstrated the potential epidemiological and cost-effective impact of Wolbachia when deployed at scale on a nationwide basis. Our findings were robust in the face of sensitivity analyses.

Nonthermal plasma as part of a novel strategy for vaccination

Vaccination has been one of the most effective health intervention mechanisms to reduce morbidity and mortality associated with infectious diseases. Vaccines stimulate the body's protective immune responses through controlled exposure to modified versions of pathogens that establish immunological memory. However, only a few diseases have effective vaccines. The biological effects of nonthermal plasma on cells suggest that plasma could play an important role in improving efficacy of existing vaccines and overcoming some of the limitations and challenges with current vaccination strategies. This review summarizes the opportunities for nonthermal plasma for immunization and therapeutic purposes.

Hidden heterogeneity and its influence on dengue vaccination impact

The CYD-TDV vaccine was recently developed to combat dengue, a mosquito-borne viral disease that afflicts millions of people each year throughout the tropical and subtropical world. Its rollout has been complicated by recent findings that vaccinees with no prior exposure to dengue virus (DENV) experience an elevated risk of severe disease in response to their first DENV infection subsequent to vaccination. As a result of these findings, guidelines for use of CYD-TDV now require serological screening prior to vaccination to establish that an individual does not fall into this high-risk category. These complications mean that the public health impact of CYD-TDV vaccination is expected to be higher in areas with higher transmission. One important practical difficulty with tailoring vaccination policy to local transmission contexts is that DENV transmission is spatially heterogeneous, even at the scale of neighborhoods or blocks within a city. This raises the question of whether models based on data that average over spatial heterogeneity in transmission could fail to capture important aspects of CYD-TDV impact in spatially heterogeneous populations. We explored this question with a deterministic model of DENV transmission and CYD-TDV vaccination in a population comprised of two communities with differing transmission intensities. Compared to the full model, a version of the model based on the average of the two communities failed to capture benefits of targeting the intervention to the high-transmission community, which resulted in greater impact in both communities than we observed under even coverage. In addition, the model based on the average of the two communities substantially overestimated impact among vaccinated individuals in the low-transmission community. In the event that the specificity of serological screening is not high, this result suggests that models that ignore spatial heterogeneity could overlook the potential for harm to this segment of the population.

Mapping global variation in dengue transmission intensity

Intervention planning for dengue requires reliable estimates of dengue transmission intensity. However, current maps of dengue risk provide estimates of disease burden or the boundaries of endemicity rather than transmission intensity. We therefore developed a global high-resolution map of dengue transmission intensity by fitting environmentally driven geospatial models to geolocated force of infection estimates derived from cross-sectional serological surveys and routine case surveillance data. We assessed the impact of interventions on dengue transmission and disease using Wolbachia-infected mosquitoes and the Sanofi-Pasteur vaccine as specific examples. We predicted high transmission intensity in all continents straddling the tropics, with hot spots in South America (Colombia, Venezuela, and Brazil), Africa (western and central African countries), and Southeast Asia (Thailand, Indonesia, and the Philippines). We estimated that 105 [95% confidence interval (CI), 95 to 114] million dengue infections occur each year with 51 (95% CI, 32 to 66) million febrile disease cases. Our analysis suggests that transmission-blocking interventions such as Wolbachia, even at intermediate efficacy (50% transmission reduction), might reduce global annual disease incidence by up to 90%. The Sanofi-Pasteur vaccine, targeting only seropositive recipients, might reduce global annual disease incidence by 20 to 30%, with the greatest impact in high-transmission settings. The transmission intensity map presented here, and made available for download, may help further assessment of the impact of dengue control interventions and prioritization of global public health efforts.

Climate change could shift disease burden from malaria to arboviruses in Africa

Malaria is a long-standing public health problem in sub-Saharan Africa, whereas arthropod-borne viruses (arboviruses) such as dengue and chikungunya cause an under-recognised burden of disease. Many human and environmental drivers affect the dynamics of vector-borne diseases. In this Personal View, we argue that the direct effects of warming temperatures are likely to promote greater environmental suitability for dengue and other arbovirus transmission by Aedes aegypti and reduce suitability for malaria transmission by Anopheles gambiae. Environmentally driven changes in disease dynamics will be complex and multifaceted, but given that current public efforts are targeted to malaria control, we highlight Ae aegypti and dengue, chikungunya, and other arboviruses as potential emerging public health threats in sub-Saharan Africa.

Tooling-up for infectious disease transmission modelling

In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be.

Ensuring the Safety of Yellow Fever Vaccination in Travelers-The Experience at a Large U.S. Academic Medical Center in Colorado

Background: Yellow fever (YF) virus has the potential to cause fatal outcomes among at-risk individuals visiting endemic areas. Vaccinating travelers who are at risk is necessary to prevent virus-related life-threatening complications. We lack data on the clinical features of persons seeking YF vaccination. We aim to describe the characteristics of a cohort of persons receiving the YF vaccine before travel. Methods: A retrospective analysis of 964 travelers receiving the YF vaccine (Stamaril^®) from Oct 2016 to Jul 2019 was performed at the University of Colorado Hospital, U.S. Percentages, means, and standard deviations were calculated. A multivariate logistic regression model was built to evaluate the association between receiving YF vaccination less than 10 days before departure and visiting friends and relatives (VFR). Results: The average age of the subjects was 39 ± 18 years with a range of nine months to 83 years. Persons who were 60 years of age and older represented 17%. Women consisted of 52%, and most of the travelers were Caucasians (64%). Travelers reported traveling to Africa (57%) or South America (40%). The primary destinations for travelers overall were Kenya (19%), Uganda (11%), and Tanzania (11%) in Africa; and Peru (14%) and Brazil (13%) in South America. The most common reasons for travel included leisure (44%), VFR (18%), and mission trips (10%). Comorbidities included a history of hematologic disorders (4%), HIV infection (2%), and diabetes mellitus (3%). The average duration between vaccine administration and travel was 43 days. Those VFR were two times more likely to receive the YF vaccination <10 days before departure. Conclusions: Identifying the type of travel, itinerary, and underlying medical conditions allows providers to administer the YF vaccine to travelers safely. There is a need to identify strategies to improve the timing of YF vaccination among VFR travelers.

The first licensed dengue vaccine: can it be used in travelers?

PURPOSE OF REVIEW

The first dengue vaccine (Dengvaxia) was endorsed by the European Medicine Agency and the US Food and Drug Administration. Given the excess risk of severe dengue in seronegative vaccinees, use is restricted to seropositive individuals. Dengvaxia confers high protection against severe dengue in seropositive vaccinees.

RECENT FINDINGS

With increasing global travel, the probability of travelers being seropositive increases. Such seropositive travelers may be at increased risk of severe dengue as a result of a second dengue infection during repeat travel. Nevertheless, the use of Dengvaxia in travelers requires a careful analysis of all the factors. Seropositive travelers only present a minority of all travelers. A validated rapid diagnostic test to screen for dengue serostatus is not yet available. Such a test should be highly specific to avoid inadvertent vaccination of seronegative individuals. The three-dose regimen precludes the use in most travelers who tend to present at travel clinics less than 6 weeks prior to departure. Furthermore, questions about potential sub-optimal immunogenicity in seropositives in nonendemic settings, and the need and timing of boosters remain unanswered.

SUMMARY

Although there could potentially be substantial protection against severe dengue in seropositive travelers, Dengvaxia is far from an ideal travel vaccine.

Enhancement of Tetravalent Immune Responses to Highly Conserved Epitopes of a Dengue Peptide Vaccine Conjugated to Polystyrene Nanoparticles

Vaccination remains the major approach to the prevention of dengue. Since the only licensed live attenuated vaccine (LAV) lacked efficacy against all four serotypes, other vaccine platforms, such as synthetic peptide vaccines, should be explored. In this study, four multi-epitope peptides (P1-P4) were designed by linking a universal T-helper epitope (PADRE or TpD) to the highly conserved CD8 T cell epitope and B cell epitope (B1 or B2) against all four DENV serotypes. The multi-epitope peptides were conjugated to polystyrene nanoparticles (PSNPs) and four nanovaccines (NP1-NP4) were constructed. Mice immunized with NP1-NP4 elicited significantly higher titers of IgG and neutralizing antibodies when compared to immunization with naked P1-P4. The immune responses in mice immunized with peptide vaccines were compared with nanovaccines using ELISA, ELISPOT, and a neutralization test based on FRNT₅₀. Among the four conjugated peptide nanovaccines, NP3 comprising the TpD T-helper epitope linked to the highly conserved B1 epitope derived from the E protein was able to elicit significant levels of IFN-γ and neutralizing antibodies to all four dengue serotypes. NP3 is a promising tetravalent synthetic peptide vaccine, but the selection of a more effective CD8⁺ T cell epitope and adjuvants to further improve the immunogenicity is warranted.