Cross-protective immunity can account for the alternating epidemic pattern of dengue virus serotypes circulating in Bangkok

Prevalence and characteristics of dengue virus co-infection in patients and mosquitoes collected from patients' houses

Co-infection with multiple DENV serotypes can affect human immune status and complicate the clinical presentation and management of dengue patients, so understanding the prevalence and dynamics of co-infection is important for effective dengue control. We aimed to identify and characterize DENV co-infection patterns in field-caught mosquitoes and dengue patients. This study was conducted in northeastern Thailand between June 2016 to August 2019. Female Aedes mosquitos collected from and around dengue patient's houses were analyzed for DENV infection and presence of serotypes using RT-PCR. DENV serotyping was successful in 154 (39.49%) of human and 165 (14.26%) of mosquito samples. Prevalence of DENV co-infection in patients and mosquitoes was 22.73% (35 cases) and 28.48% (47 samples), respectively. Co-infection with multiple serotypes were double (human 88.57%, mosquito 89.36%), triple (human 5.72%, mosquito 10.64%) and quadruple (human 5.72%, mosquito 0%) infections. Concurrent infection was different between hosts and concurrence patterns of DENV serotype in each host mostly composed of the predominant serotype of the detected year. This is the first report that show DENV co-infection patterns in field-caught mosquito and in dengue fever patients with combinations of triple and quadruple serotypes in Thailand. These finding are potentially useful for understanding shifts in serotypes, concurrent DENV infection patterns, vaccine development, and further research on the ability of vectors to transmit multiple serotypes.

Impact of pre-existing cross-reactive antibodies on cyclic dengue outbreaks in the hyperendemic region of Bali, Indonesia

The four serotypes of the dengue virus (DENV) cause a range of diseases ranging from mild fever to severe conditions. Understanding the immunological interactions among the four serotypes is crucial in comprehending the dynamics of serotype shifting during outbreaks in areas where all four serotypes co-circulate. Hence, we evaluated the neutralizing antibody and antibody-dependent enhancement responses against the four DENV serotypes using acute-phase plasma samples collected from 48 laboratory-confirmed dengue patients during a dengue outbreak in Bali, Indonesia in 2022. Employing single-round infectious particles to exclusively investigate immunogenicity to the structural surface proteins of DENV, which are the targets of antibodies, we found that individuals with a probable prior history of DENV-1 infection exhibited increased susceptibility to secondary DENV-3 infection, attributed to cross-reactive antibodies with limited neutralizing activity against DENV-3 (geometric mean 50 % neutralization titer (GMNT50) = 47.6 ± 11.5). This susceptibility was evident in vitro, with a mean fold enhancement of 28.4 ± 33.9. Neutralization titers against DENV-3 were significantly lower compared to other serotypes (DENV-1 GMNT50 = 678.1 ± 9.0; DENV-2 GMNT50 = 210.5 ± 8.7; DENV-4 GMNT50 = 95.14 ± 7.0). We demonstrate that prior immunity to one serotype provides limited cross-protection against the other serotypes, influencing the dominant serotype in subsequent outbreaks. These findings underscore the complexity of dengue immunity and its implications for vaccine design and transmission dynamics in hyperendemic regions.

Climate, demography, immunology, and virology combine to drive two decades of dengue virus dynamics in Cambodia

The incidence of dengue virus disease has increased globally across the past half-century, with highest number of cases ever reported in 2019 and again in 2023. We analyzed climatological, epidemiological, and phylogenomic data to investigate drivers of two decades of dengue in Cambodia, an understudied endemic setting. Using epidemiological models fit to a 19-y dataset, we first demonstrate that climate-driven transmission alone is insufficient to explain three epidemics across the time series. We then use wavelet decomposition to highlight enhanced annual and multiannual synchronicity in dengue cycles between provinces in epidemic years, suggesting a role for climate in homogenizing dynamics across space and time. Assuming reported cases correspond to symptomatic secondary infections, we next use an age-structured catalytic model to estimate a declining force of infection for dengue through time, which elevates the mean age of reported cases in Cambodia. Reported cases in >70-y-old individuals in the 2019 epidemic are best explained when also allowing for waning multitypic immunity and repeat symptomatic infections in older patients. We support this work with phylogenetic analysis of 192 dengue virus (DENV) genomes that we sequenced between 2019 and 2022, which document emergence of DENV-2 Cosmopolitan Genotype-II into Cambodia. This lineage demonstrates phylogenetic homogeneity across wide geographic areas, consistent with invasion behavior and in contrast to high phylogenetic diversity exhibited by endemic DENV-1. Finally, we simulate an age-structured, mechanistic model of dengue dynamics to demonstrate how expansion of an antigenically distinct lineage that evades preexisting multitypic immunity effectively reproduces the older-age infections witnessed in our data.

Estimating dengue burden among family contacts through cluster investigation around probable cases in 2022 and 2023 in the Central Region, Burkina Faso

BACKGROUND

In 2023, Burkina Faso experienced the largest dengue epidemic ever in Africa. This study aimed to estimate the prevalence of symptomatic, subclinical, and asymptomatic dengue and determine the associated factors among adult contacts of dengue in the Central Region, Burkina Faso.

METHODS

This cross-sectional study included contacts of dengue probable cases through cluster sampling in 2022-2023. These suspected cases that tested positive were identified from the five health facilities (Pissy CMA, Saaba CM, Kossodo CMA, Samandin CM, and Marcoussis CSPS) that reported the highest number of cases in 2021 per district. All participants underwent dengue and malaria rapid diagnostic tests (RDT). Samples positive for non-structural 1 protein antigen (AgNS1) and/or immunoglobulin M (IgM) were tested for serotype detection by reverse transcription polymerase chain reaction (RT-PCR). Binary logistic regression was done to identify the determinants of asymptomatic, subclinical, and symptomatic dengue among contacts of probable dengue cases.

RESULTS

A total of 484 contacts were included, mostly in 2023 (75.2%). Most participants were females (58.6%), residing (24.3%) and passing their daytime (23.1%) in Saaba. The overall prevalence of dengue was estimated at 15.1% [95% confidence interval (CI): 12.0-18.6%], representing cases not seeking care in hospitals. Asymptomatic cases represented 2.9% (95% CI: 1.6-4.8%). Subclinical and symptomatic cases accounted for 6.0% (95% CI: 4.1-8.5%) and 6.2% (95% CI: 4.2-8.7%), respectively. Of the 58 samples tested by RT-PCR, 10 were confirmed for serotype 3 in 2023. Malaria cases were estimated at 5.6% (95% CI: 3.7-8.0%). After adjustment, participants claiming that a virus transmits dengue were likelier to have asymptomatic dengue [adjusted odds ratio (aOR) = 7.1, 95% CI: 2.4-21.0]. From the multivariable analysis, subclinical dengue was statistically associated with being included in the study in 2023 (aOR = 30.2, 95% CI: 2.0-455.5) and spending the daytime at Arrondissement 4 (aOR = 11.5, 95% CI: 1.0-131.0). After adjustment, symptomatic dengue was associated with living less than 50 m away from cultivated land (aOR = 2.8, 95% CI: 1.1-6.9) and living less than 50 m from a stretch of water (aOR = 0.1, 95% CI: 0.0-0.6).

CONCLUSIONS

The overall burden of dengue among populations not seeking care in hospitals was quite high, with few asymptomatic cases. Efforts to manage dengue cases should also target non-hospital cases and raise population awareness. The 2023 epidemic could be due to dengue virus (DENV)-3.

Microclimate factors related to dengue virus burden clusters in two endemic towns of Mexico

In dengue-endemic areas, transmission control is limited by the difficulty of achieving sufficient coverage and sustainability of interventions. To maximize the effectiveness of interventions, areas with higher transmission could be identified and prioritized. The aim was to identify burden clusters of Dengue virus (DENV) infection and evaluate their association with microclimatic factors in two endemic towns from southern Mexico. Information from a prospective population cohort study (2·5 years of follow-up) was used, microclimatic variables were calculated from satellite information, and a cross-sectional design was conducted to evaluate the relationship between the outcome and microclimatic variables in the five surveys. Spatial clustering was observed in specific geographic areas at different periods. Both, land surface temperature (aPR 0·945; IC95% 0·895-0·996) and soil humidity (aPR 3·018; IC95% 1·013-8·994), were independently associated with DENV burden clusters. These findings can help health authorities design focused dengue surveillance and control activities in dengue endemic areas.

Travel surveillance uncovers dengue virus dynamics and introductions in the Caribbean

Dengue is the most prevalent mosquito-borne viral disease in humans, and cases are continuing to rise globally. In particular, islands in the Caribbean have experienced more frequent outbreaks, and all four dengue virus (DENV) serotypes have been reported in the region, leading to hyperendemicity and increased rates of severe disease. However, there is significant variability regarding virus surveillance and reporting between islands, making it difficult to obtain an accurate understanding of the epidemiological patterns in the Caribbean. To investigate this, we used travel surveillance and genomic epidemiology to reconstruct outbreak dynamics, DENV serotype turnover, and patterns of spread within the region from 2009-2022. We uncovered two recent DENV-3 introductions from Asia, one of which resulted in a large outbreak in Cuba, which was previously under-reported. We also show that while outbreaks can be synchronized between islands, they are often caused by different serotypes. Our study highlights the importance of surveillance of infected travelers to provide a snapshot of local introductions and transmission in areas with limited local surveillance and suggests that the recent DENV-3 introductions may pose a major public health threat in the region.

The Spatiotemporal Distribution and Molecular Characterization of Circulating Dengue Virus Serotypes/Genotypes in Senegal from 2019 to 2023

Dengue virus is becoming a major public health threat worldwide, principally in Africa. From 2016 to 2020, 23 outbreaks were reported in Africa, principally in West Africa. In Senegal, dengue outbreaks have been reported yearly since 2017. Data about the circulating serotypes and their spatial and temporal distribution were limited to outbreaks that occurred between 2017 and 2018. Herein, we describe up-to-date molecular surveillance of circulating DENV serotypes in Senegal between 2019 to 2023 and their temporal and spatial distribution around the country. For this purpose, suspected DENV-positive samples were collected and subjected to dengue detection and serotyping using RT-qPCR methods. Positive samples were used for temporal and spatial mapping. A subset of DENV+ samples were then sequenced and subjected to phylogenetic analysis. Results show a co-circulation of three DENV serotypes with an overall predominance of DENV-3. In terms of abundance, DENV-3 is followed by DENV-1, with scarce cases of DENV-2 from February 2019 to February 2022. Interestingly, data show the extinction of both serotype 1 and serotype 2 and the only circulation of DENV-3 from March 2022 to February 2023. At the genotype level, the analysis shows that sequenced strains belong to same genotype as previously described: Senegalese DENV-1 strains belong to genotype V, DENV-2 strains to the cosmopolitan genotype, and DENV-3 strains to Genotype III. Interestingly, newly obtained DENV 1-3 sequences clustered in different clades within genotypes. This co-circulation of strains belonging to different clades could have an effect on virus epidemiology and transmission dynamics. Overall, our results highlight DENV serotype replacement by DENV-3, accompanied by a wider geographic distribution, in Senegal. These results highlight the importance of virus genomic surveillance and call for further viral fitness studies using both in vitro and in vivo models, as well as in-depth phylogeographic studies to uncover the virus dispersal patterns across the country.

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.

Effects of boosting and waning in highly exposed populations on dengue epidemic dynamics

Sequential infection with multiple dengue virus (DENV) serotypes is thought to induce enduring protection against dengue disease. However, long-term antibody waning has been observed after repeated DENV infection. Here, we provide evidence that highly immune Nicaraguan children and adults (n = 4478) experience boosting and waning of antibodies during and after major Zika and dengue epidemics. We develop a susceptible-infected-recovered-susceptible (SIRS-type) model that tracks immunity by titer rather than number of infections to show that boosts in highly immune individuals can contribute to herd immunity, delaying their susceptibility to transmissible infection. In contrast, our model of lifelong immunity in highly immune individuals, as previously assumed, results in complete disease eradication after introduction. Periodic epidemics under this scenario can only be sustained with a constant influx of infected individuals into the population or a high basic reproductive number. We also find that Zika virus infection can boost DENV immunity and produce delays and then surges in dengue epidemics, as observed with real epidemiological data. This work provides insight into factors shaping periodicity in dengue incidence and may inform vaccine efforts to maintain population immunity.

Temporary Cross-Immunity as a Plausible Driver of Asynchronous Cycles of Dengue Serotypes

Many infectious diseases exist as multiple variants, with interactions between variants potentially driving epidemiological dynamics. These diseases include dengue, which infects hundreds of millions of people every year and exhibits complex multi-serotype dynamics. Antibodies produced in response to primary infection by one of the four dengue serotypes can produce a period of temporary cross-immunity (TCI) to infection by other serotypes. After this period, the remaining antibodies can facilitate the entry of heterologous serotypes into target cells, thus enhancing severity of secondary infection by a heterologous serotype. This represents antibody-dependent enhancement (ADE). In this study, we analyze an epidemiological model to provide novel insights into the importance of TCI and ADE in producing cyclic outbreaks of dengue serotypes. Our analyses reveal that without TCI, such cyclic outbreaks are synchronous across serotypes and only occur when ADE produces high transmission rates. In contrast, the presence of TCI allows asynchronous cycles of serotypes by inducing a time lag between recovery from primary infection by one serotype and secondary infection by another, with such cycles able to occur without ADE. Our results suggest that TCI is a fundamental driver of asynchronous cycles of dengue serotypes and possibly other multi-variant diseases.

Common patterns between dengue cases, climate, and local environmental variables in Costa Rica: A wavelet approach

Dengue transmission poses significant challenges for public health authorities worldwide due to its susceptibility to various factors, including environmental and climate variability, affecting its incidence and geographic spread. This study focuses on Costa Rica, a country characterized by diverse microclimates nearby, where dengue has been endemic since its introduction in 1993. Using wavelet coherence and clustering analysis, we performed a time-series analysis to uncover the intricate connections between climate, local environmental factors, and dengue occurrences. The findings indicate that multiannual dengue frequency (3 yr) is correlated with the Oceanic Niño Index and the Tropical North Atlantic Index. This association is particularly prominent in cantons located along the North and South Pacific Coast, as well as in the Central cantons of the country. Furthermore, the time series of these climate indices exhibit a leading phase of approximately nine months ahead of dengue cases. Additionally, the clustering analysis uncovers non-contiguous groups of cantons that exhibit similar correlation patterns, irrespective of their proximity or adjacency. This highlights the significance of climate factors in influencing dengue dynamics across diverse regions, regardless of spatial closeness or distance between them. On the other hand, the annual dengue frequency was correlated with local environmental indices. A persistent correlation between dengue cases and local environmental variables is observed over time in the North Pacific and the Central Region of the country's Northwest, with environmental factors leading by less than three months. These findings contribute to understanding dengue transmission's spatial and temporal dynamics in Costa Rica, highlighting the importance of climate and local environmental factors in dengue surveillance and control efforts.

Neutralizing antibodies from prior exposure to dengue virus negatively correlate with viremia on re-infection

BACKGROUND

India is hyperendemic to dengue and over 50% of adults are seropositive. There is limited information on the association between neutralizing antibody profiles from prior exposure and viral RNA levels during subsequent infection.

METHODS

Samples collected from patients with febrile illness was used to assess seropositivity by indirect ELISA. Dengue virus (DENV) RNA copy numbers were estimated by quantitative RT-PCR and serotype of the infecting DENV was determined by nested PCR. Focus reduction neutralizing antibody titer (FRNT) assay was established using Indian isolates to measure the levels of neutralizing antibodies and also to assess the cross-reactivity to related flaviviruses namely Zika virus (ZIKV), Japanese encephalitis virus (JEV) and West Nile virus (WNV).

RESULTS

In this cross-sectional study, we show that dengue seropositivity increased from 52% in the 0-15 years group to 89% in >45 years group. Antibody levels negatively correlate with dengue RNAemia on the day of sample collection and higher RNAemia is observed in primary dengue as compared to secondary dengue. The geometric mean FRNT50 titers for DENV-2 is significantly higher as compared to the other three DENV serotypes. We observe cross-reactivity with ZIKV and significantly lower or no neutralizing antibodies against JEV and WNV. The FRNT50 values for international isolates of DENV-1, DENV-3 and DENV-4 is significantly lower as compared to Indian isolates.

CONCLUSIONS

Majority of the adult population in India have neutralizing antibodies to all the four DENV serotypes which correlates with reduced RNAemia during subsequent infection suggesting that antibodies can be considered as a good correlate of protection.

Convergent trends and spatiotemporal patterns of Aedes-borne arboviruses in Mexico and Central America

BACKGROUND

Aedes-borne arboviruses cause both seasonal epidemics and emerging outbreaks with a significant impact on global health. These viruses share mosquito vector species, often infecting the same host population within overlapping geographic regions. Thus, comparative analyses of the virus evolutionary and epidemiological dynamics across spatial and temporal scales could reveal convergent trends.

METHODOLOGY/PRINCIPAL FINDINGS

Focusing on Mexico as a case study, we generated novel chikungunya and dengue (CHIKV, DENV-1 and DENV-2) virus genomes from an epidemiological surveillance-derived historical sample collection, and analysed them together with longitudinally-collected genome and epidemiological data from the Americas. Aedes-borne arboviruses endemically circulating within the country were found to be introduced multiple times from lineages predominantly sampled from the Caribbean and Central America. For CHIKV, at least thirteen introductions were inferred over a year, with six of these leading to persistent transmission chains. For both DENV-1 and DENV-2, at least seven introductions were inferred over a decade.

CONCLUSIONS/SIGNIFICANCE

Our results suggest that CHIKV, DENV-1 and DENV-2 in Mexico share evolutionary and epidemiological trajectories. The southwest region of the country was determined to be the most likely location for viral introductions from abroad, with a subsequent spread into the Pacific coast towards the north of Mexico. Virus diffusion patterns observed across the country are likely driven by multiple factors, including mobility linked to human migration from Central towards North America. Considering Mexico's geographic positioning displaying a high human mobility across borders, our results prompt the need to better understand the role of anthropogenic factors in the transmission dynamics of Aedes-borne arboviruses, particularly linked to land-based human migration.

Applying a multi-strain dengue model to epidemics data

Dengue disease transmission is a complex vector-borne disease, mainly due to the co-circulation of four serotypes of the virus. Mathematical models have proved to be a useful tool to understand the complexity of this disease. In this work, we extend the model studied by Esteva et al., 2003, originally proposed for two serotypes, to four circulating serotypes. Using epidemic data of dengue fever in Iquitos (Peru) and San Juan (Puerto Rico), we estimate numerically the co-circulation parameter values for selected outbreaks using a bootstrap method, and we also obtained the Basic Reproduction Number, R₀, for each serotype, using both analytical calculations and numerical simulations. Our results indicate that the impact of co-circulation of serotypes in population dynamics of dengue infection is such that there is a reduced effect from DENV-3 to DENV-4 in comparison to no-cross effect for epidemics in Iquitos. Concerning San Juan epidemics, also comparing to no-cross effect, we also observed a reduced effect from the predominant serotype DENV-3 to both DENV-2 and DENV-1 epidemics neglecting the very small number of cases of DENV-4.

Evolutionary dynamics of dengue virus in India

More than a hundred thousand dengue cases are diagnosed in India annually, and about half of the country's population carries dengue virus-specific antibodies. Dengue propagates and adapts to the selection pressures imposed by a multitude of factors that can lead to the emergence of new variants. Yet, there has been no systematic analysis of the evolution of the dengue virus in the country. Here, we present a comprehensive analysis of all DENV gene sequences collected between 1956 and 2018 from India. We examine the spatio-temporal dynamics of India-specific genotypes, their evolutionary relationship with global and local dengue virus strains, interserotype dynamics and their divergence from the vaccine strains. Our analysis highlights the co-circulation of all DENV serotypes in India with cyclical outbreaks every 3-4 years. Since 2000, genotype III of DENV-1, cosmopolitan genotype of DENV-2, genotype III of DENV-3 and genotype I of DENV-4 have been dominating across the country. Substitution rates are comparable across the serotypes, suggesting a lack of serotype-specific evolutionary divergence. Yet, the envelope (E) protein displays strong signatures of evolution under immune selection. Apart from drifting away from its ancestors and other contemporary serotypes in general, we find evidence for recurring interserotype drift towards each other, suggesting selection via cross-reactive antibody-dependent enhancement. We identify the emergence of the highly divergent DENV-4-Id lineage in South India, which has acquired half of all E gene mutations in the antigenic sites. Moreover, the DENV-4-Id is drifting towards DENV-1 and DENV-3 clades, suggesting the role of cross-reactive antibodies in its evolution. Due to the regional restriction of the Indian genotypes and immunity-driven virus evolution in the country, ~50% of all E gene differences with the current vaccines are focused on the antigenic sites. Our study shows how the dengue virus evolution in India is being shaped in complex ways.

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.

Full genome analysis of circulating DENV-2 in Senegal reveals a regional diversification into separate clades

To assess the genetic diversity of circulating dengue virus 2 (DENV-2) in Senegal, we analyzed nine newly generated complete genomes of strains isolated during the 2018 outbreaks and 06 sequences obtained in 2018 and 2019 from Thiès and Rosso, respectively. Phylogenetic analyses revealed that Senegalese strains belonged to the cosmopolitan genotype of DENV-2, but we observed intragenotype variability leading to a divergence in two clades associated with specific geographic distribution. We report two DENV-2 variants belonging to two distinct clades. Isolates from the "Northern clade" (n = 8) harbored three nonsynonymous mutations (V1183M, R1405K, P2266T) located respectively on NS2A, NS2B, and NS4A, while isolates from the "Western clade" (n = 7) had two nonsynonymous mutations (V1185E, V3214E) located respectively in the NS2A and NS5 genes. These findings call for phylogeographic analysis to investigate routes of introductions, dispersal patterns, and in-depth in vitro and functional study to elucidate the impact of observed mutations on viral fitness, spread, epidemiology, and pathology.

Considering humans as habitat reveals evidence of successional disease ecology among human pathogens

The realization that ecological principles play an important role in infectious disease dynamics has led to a renaissance in epidemiological theory. Ideas from ecological succession theory have begun to inform an understanding of the relationship between the individual microbiome and health but have not yet been applied to investigate broader, population-level epidemiological dynamics. We consider human hosts as habitat and apply ideas from succession to immune memory and multi-pathogen dynamics in populations. We demonstrate that ecologically meaningful life history characteristics of pathogens and parasites, rather than epidemiological features alone, are likely to play a meaningful role in determining the age at which people have the greatest probability of being infected. Our results indicate the potential importance of microbiome succession in determining disease incidence and highlight the need to explore how pathogen life history traits and host ecology influence successional dynamics. We conclude by exploring some of the implications that inclusion of successional theory might have for understanding the ecology of diseases and their hosts.

This study explores the analogy between ecological succession in terrestrial ecosystems and infections in a human-host landscape over time, showing how the ecosystem of long-term multi-pathogen dynamics within and among hosts may be a critical missing consideration in understanding epidemiology.

Mathematical modeling in perspective of vector-borne viral infections: a review

Background

Viral diseases are highly widespread infections caused by viruses. These viruses are passing from one human to other humans through a certain medium. The medium might be mosquito, animal, reservoir and food, etc. Here, the population of both human and mosquito vectors are important.

Main body of the abstract

The main objectives are here to introduce the historical perspective of mathematical modeling, enable the mathematical modeler to understand the basic mathematical theory behind this and present a systematic review on mathematical modeling for four vector-borne viral diseases using the deterministic approach. Furthermore, we also introduced other mathematical techniques to deal with vector-borne diseases. Mathematical models could help forecast the infectious population of humans and vectors during the outbreak.

Short conclusion

This study will be helpful for mathematical modelers in vector-borne diseases and ready-made material in the review for future advancement in the subject. This study will not only benefit vector-borne conditions but will enable ideas for other illnesses.

Beneath the surface: Amino acid variation underlying two decades of dengue virus antigenic dynamics in Bangkok, Thailand

Neutralizing antibodies are important correlates of protection against dengue. Yet, determinants of variation in neutralization across strains within the four dengue virus serotypes (DENV1-4) is imperfectly understood. Studies focus on structural DENV proteins, especially the envelope (E), the primary target of anti-DENV antibodies. Although changes in immune recognition (antigenicity) are often attributed to variation in epitope residues, viral processes influencing conformation and epitope accessibility also affect neutralizability, suggesting possible modulating roles of nonstructural proteins. We estimated effects of residue changes in all 10 DENV proteins on antigenic distances between 348 DENV collected from individuals living in Bangkok, Thailand (1994-2014). Antigenic distances were derived from response of each virus to a panel of twenty non-human primate antisera. Across 100 estimations, excluding 10% of virus pairs each time, 77 of 295 positions with residue variability in E consistently conferred antigenic effects; 52 were within ±3 sites of known binding sites of neutralizing human monoclonal antibodies, exceeding expectations from random assignments of effects to sites (p = 0.037). Effects were also identified for 16 sites on the stem/anchor of E which were only recently shown to become exposed under physiological conditions. For all proteins, except nonstructural protein 2A (NS2A), root-mean-squared-error (RMSE) in predicting distances between pairs held out in each estimation did not outperform sequences of equal length derived from all proteins or E, suggesting that antigenic signals present were likely through linkage with E. Adjusted for E, we identified 62/219 sites embedding the excess signals in NS2A. Concatenating these sites to E additionally explained 3.4% to 4.0% of observed variance in antigenic distances compared to E alone (50.5% to 50.8%); RMSE outperformed concatenating E with sites from any protein of the virus (ΔRMSE, 95%IQR: 0.01, 0.05). Our results support examining antigenic determinants beyond the DENV surface.

Dengue viruses, even of the same serotype, are differentially recognized by preexisting antibodies of individuals. With antibody levels being an important indicator of infection risk and pathogenicity, understanding mechanisms underlying these differences are crucial for vaccine design and development. Investigations have primarily targeted surface regions of the envelope protein (E) where virus-antibody interactions were thought to primarily occur. However, the roles of non-surface regions of the E protein as well as nonstructural proteins has been limited. We looked at the entire virus to identify associations between specific changes in the protein sequence and differences in how viruses were recognized by antibodies. In addition to recovering known determinants on the surface, we found signals in other areas on the structural building blocks of the virus. We also identified additional signals on specific areas of a protein that does not form structures of the virus but orchestrate virus formation. Our results point towards broadening the frame of investigation to gain a more comprehensive understanding of mechanisms giving rise to antibody recognition of dengue viruses, and may aid the design and evaluation of vaccines and/or assays to characterize dengue immunity.

Spatio-temporal dynamics of dengue-related deaths and associated factors

Since the reintroduction of dengue viruses in 1987, Sao Paulo State (SP), Brazil, has experienced recurrent epidemics in a growing number of municipalities, each time with more cases and deaths. In the present study, we investigated the spatio-temporal dynamics of dengue-related deaths and associated factors in SP. This was an ecological study with spatial and temporal components, based on notified dengue-related deaths in the municipalities of SP between 2007 and 2017. A latent Gaussian Bayesian model with Poisson probability distribution was used to estimate the standardized mortality ratios (SMR) for dengue and relative risks (RR) for the socioeconomic, demographic, healthcare-related, and epidemiological factors considered. Epidemiological factors included the annual information on the number of circulating serotypes. A total of 1,019 dengue-related deaths (0.22 per 100,000 inhabitant-years) between 2007 and 2017 were confirmed in SP by laboratory testing. Mortality increased with age, peaking at 70 years or older (1.41 deaths per 100,000 inhabitant-years). Mortality was highest in 2015, and the highest SMR values were found in the North, Northwest, West, and coastal regions of SP. An increase of one circulating serotype, one standard deviation in the number of years with cases, and one standard deviation in the degree of urbanization were associated with increases of 75, 35, and 45% in the risk of death from dengue, respectively. The risk of death from dengue increased with age, and the distribution of deaths was heterogeneous in space and time. The positive relationship found between the number of dengue serotypes circulating and years with cases at the municipality/micro-region level indicates that this information can be used to identify risk areas, intensify surveillance and control measures, and organize healthcare to better respond to this disease.

Global Evolutionary History and Dynamics of Dengue Viruses Inferred from Whole Genome Sequences

Dengue is an arboviral disease caused by dengue virus (DENV), leading to approximately 25,000 deaths/year and with over 40% of the world’s population at risk. Increased international travel and trade, poorly regulated urban expansion, and warming global temperatures have expanded the geographic range and incidence of the virus in recent decades. This study used phylogenetic and selection pressure analyses to investigate trends in DENV evolution, using whole genome coding sequences from publicly available databases alongside newly sequenced isolates collected between 1963–1997 from Southeast Asia and the Pacific. Results revealed very similar phylogenetic relationships when using the envelope gene and the whole genome coding sequences. Although DENV evolution is predominantly driven by negative selection, a number of amino acid sites undergoing positive selection were found across the genome, with the majority located in the envelope and NS5 genes. Some genotypes appear to be diversifying faster than others within each serotype. The results from this research improve our understanding of DENV evolution, with implications for disease control efforts such as Wolbachia-based biocontrol and vaccine design.

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.

The Distribution of Dengue Virus Serotype in Quang Nam Province (Vietnam) during the Outbreak in 2018

Objectives: Quang Nam province in the Centre of Vietnam has faced an outbreak of dengue hemorrhagic fever (DHF) in 2018. Although DHF is a recurrent disease in this area, no epidemiological and microbiological reports on dengue virus serotypes have been conducted mainly due to lack of facilities for such a kind of advanced surveillance. The aim of this study was to detect different dengue virus serotypes in patients' blood samples. Design and Methods: Suspected cases living in Quang Nam province (Vietnam) and presenting clinical and hematological signs of dengue hemorrhagic fever were included in the study. The screening was performed, and the results were compared by using two methodologies: RT real-time PCR (RT-rPCR) and the Dengue NS1 rapid test. Results: From December 2018 to February 2019, looking both at RT-rPCR [+] and NS1 [+] methodologies, a total of 488 patients were screened and 336 were positive for dengue virus detection (74 children and 262 adults); 273 of these patients (81.3%) underwent viral serotype identification as follows: 12.82% (35/273) D1 serotype, 17.95% (49/273) D2, 0.37% (1/273) D3, 68.50 (187/283) D4, and 0.37% (1/273) D2+D4 serotypes. The RT-rPCR outcomes showed higher sensitivity during the first three days of infection compared to NS1 (92.3% vs. 89.7%). The NS1 increased sensitivity after the first 3 days whilst the RT-rPCR decreased. Conclusions: Advanced surveillance with dengue virus serotypes identification, if performed routinely, may help to predict and prevent further DHF epidemics based on the exposure of the different serotypes during different periods that lead to the intensification of disease severity as a consequence of antibody-dependent enhancement (ADE).

The effect of human vaccination behaviour on strain competition in an infectious disease: An imitation dynamic approach

Strain competition plays an important role in shaping the dynamics of multiple pathogen outbreaks in a population. Competition may lead to exclusion of some pathogens, while it may influence the invasion of an emerging mutant in the population. However, little emphasis has been given to understand the influence of human vaccination choice on pathogen competition or strain invasion for vaccine-preventable infectious diseases. Coupling game dynamic framework of vaccination choice and compartmental disease transmission model of two strains, we explore invasion and persistence of a mutant in the population despite having a lower reproduction rate than the resident one. We illustrate that higher perceived strain severity and lower perceived vaccine efficacy are necessary conditions for the persistence of a mutant strain. The numerical simulation also extends these invasion and persistence analyses under asymmetric cross-protective immunity of these strains. We show that the dynamics of this cross-immunity model under human vaccination choices is determined by the interplay of parameters defining the cross-immune response function, perceived risk of infection, and vaccine efficacy, and it can exhibit invasion and persistence of mutant strain, even complete exclusion of resident strain in the regime of sufficiently high perceived risk. We conclude by discussing public health implications of the results, that proper risk communication in public about the severity of the disease is an important task to reduce the chance of mutant invasion. Thus, understanding pathogen competitions under social interactions and choices may be an important component for policymakers for strategic decision-making.

Differential heterologous neutralisation profile against strains within DENV-3 genotype II

The dengue virus type 3 (DENV-3) homotypic outbreak cycles reported in Klang Valley, Malaysia in 1992–1995 and 2002 demonstrated different epidemic magnitude and duration. These outbreak cycles were caused by two closely related strains of viruses within the DENV-3 genotype II (DENV-3/II). The role of viral genotypic diversity and factors that could have influenced this phenomenon were investigated. The serum neutralisation sensitivity of DEN3/II strains responsible for the DENV-3 outbreak cycles in 1992–1995 and 2002 were examined. Representative virus isolates from the respective outbreaks were subjected to virus neutralisation assay using identified sera of patients with homotypic (DENV-3) or heterotypic dengue infections (DENV-1 and DENV-2). Results from the study suggested that isolates representing DENV-3/II group E (DENV-3/II-E) from the 1992–1995 outbreak and DENV-3/II group F (DENV-3/II-F) from the 2002 outbreak were neutralised at similar capacity (intergenotypic differences <2-fold) by sera of patients infected with DENV-3, DENV-1 and DENV-2/Asian genotypes. Sera of the DENV-2/Cosmopolitan infection efficiently neutralised DENV-3/II-F (FRNT₅₀ = 508.0) at a similar neutralisation capacity against its own homotypic serotype, DENV-2 (FRNT₅₀ = 452.5), but not against DENV-3/II-E (FRNT₅₀ = 100.8). The different neutralisation sensitivities of DENV-3/II strains towards the cross-reacting DENV-2 heterotypic immunity could play a role in shaping the DENV-3 recurring outbreaks pattern in Malaysia. Two genetic variations, E-132 (H/Y) and E-479 (A/V) were identified on the envelope protein of DENV-3/II-E and DENV-3/II-F, respectively. The E-132 variation was predicted to affect the protein stability. A more extensive study, however, on the implication of the naturally occurring genetic variations within closely related DENV genotypes on the neutralisation profile and protective immunity would be needed for a better understanding of the DENV spread pattern in a hyperendemic setting.

Antigenic evolution of dengue viruses over 20 years

Infection with one of dengue viruses 1 to 4 (DENV1-4) induces protective antibodies against homotypic infection. However, a notable feature of dengue viruses is the ability to use preexisting heterotypic antibodies to infect Fcγ receptor–bearing immune cells, leading to higher viral load and immunopathological events that augment disease. We tracked the antigenic dynamics of each DENV serotype by using 1944 sequenced isolates from Bangkok, Thailand, between 1994 and 2014 (348 strains), in comparison with regional and global DENV antigenic diversity (64 strains). Over the course of 20 years, the Thailand DENV serotypes gradually evolved away from one another. However, for brief periods, the serotypes increased in similarity, with corresponding changes in epidemic magnitude. Antigenic evolution within a genotype involved a trade-off between two types of antigenic change (within-serotype and between-serotype), whereas genotype replacement resulted in antigenic change away from all serotypes. These findings provide insights into theorized dynamics in antigenic evolution.

The Hard Lessons and Shifting Modeling Trends of COVID-19 Dynamics: Multiresolution Modeling Approach

The COVID-19 pandemic has placed epidemiologists, modelers, and policy makers at the forefront of the global discussion of how to control the spread of coronavirus. The main challenges confronting modelling approaches include real-time projections of changes in the numbers of cases, hospitalizations, and fatalities, the consequences of public health policy, the understanding of how best to implement varied non-pharmaceutical interventions and potential vaccination strategies, now that vaccines are available for distribution. Here, we: (i) review carefully selected literature on COVID-19 modeling to identify challenges associated with developing appropriate models along with collecting the fine-tuned data, (ii) use the identified challenges to suggest prospective modeling frameworks through which adaptive interventions such as vaccine strategies and the uses of diagnostic tests can be evaluated, and (iii) provide a novel Multiresolution Modeling Framework which constructs a multi-objective optimization problem by considering relevant stakeholders’ participatory perspective to carry out epidemic nowcasting and future prediction. Consolidating our understanding of model approaches to COVID-19 will assist policy makers in designing interventions that are not only maximally effective but also economically beneficial.

Dengue and Zika virus infections in children elicit cross-reactive protective and enhancing antibodies that persist long term

[Figure: see text].

Genetic Diversity of Dengue Virus in Clinical Specimens from Bangkok, Thailand, during 2018-2020: Co-Circulation of All Four Serotypes with Multiple Genotypes and/or Clades

Dengue is an arboviral disease highly endemic in Bangkok, Thailand. To characterize the current genetic diversity of dengue virus (DENV), we recruited patients with suspected DENV infection at the Hospital for Tropical Diseases, Bangkok, during 2018-2020. We determined complete nucleotide sequences of the DENV envelope region for 111 of 276 participant serum samples. All four DENV serotypes were detected, with the highest proportion being DENV-1. Although all DENV-1 sequences were genotype I, our DENV-1 sequences were divided into four distinct clades with different distributions in Asian countries. Two genotypes of DENV-2 were identified, Asian I and Cosmopolitan, which were further divided into two and three distinct clades, respectively. In DENV-3, in addition to the previously dominant genotype III, a cluster of 6 genotype I viruses only rarely reported in Thailand was also observed. All of the DENV-4 viruses belonged to genotype I, but they were separated into three distinct clades. These results indicated that all four serotypes of DENV with multiple genotypes and/or clades co-circulate in Bangkok. Continuous investigation of DENV is warranted to further determine the relationship between DENV within Thailand and neighboring countries in Southeast Asia and Asia.

Molecular epidemiology of dengue in North Kalimantan, a province with the highest incidence rates in Indonesia in 2019

OBJECTIVES

Dengue is endemic to Indonesia, a country that has largely varied geographical and demographic conditions across different regions. In 2019, dengue epidemic occurred in North Kalimantan province and recorded as the highest incidence rate in Indonesia. This study aims to investigate the molecular epidemiology of dengue during outbreak in the province and compare the epidemiological characteristics between two cities/towns in North Kalimantan, namely Malinau, an inland town surrounded by a dense rainforest, and Tarakan, an island city.

METHODS

A cross sectional study was conducted between September 2018 and July 2019. Dengue-like illness patients were recruited in hospitals and tested for dengue NS1 and IgG/IgM. Serological prevalence was measured using IgG ELISA, dengue virus (DENV) serotyping was conducted using RT-PCR and Envelope gene sequencing was performed to infer the virus origins and phylogeny. Clinical, demographical, and diagnostics data were also recorded and analyzed.

RESULTS

We recruited 523 patients, 261 from Malinau and 262 from Tarakan. Among them, 349 patients were confirmed dengue. Cases in Malinau had a higher proportion of confirmed dengue (82.0%) compared to those in Tarakan (51.5%). Cases in Malinau were more likely to be dengue hemorrhagic fever with more severe hematological features compared to those in Tarakan. All four DENV serotypes were detected in both cities, the most prevalent serotype being DENV-2. The genetic characteristics of the viruses in the two towns was similar except for DENV-3. No sylvatic DENV was detected as well as alphaviruses and non-dengue flaviviruses during the outbreak.

CONCLUSIONS

The molecular epidemiology of dengue in North Kalimantan revealed the similar virological characteristics but different clinical and demographic aspects in Malinau and Tarakan. The distinct dengue dynamics between different regions of Indonesia is prominent and this knowledge will be important for understanding future patterns of DENV transmission in the region.

Optimal Control of Dengue Transmission with Vaccination

Dengue disease is caused by four serotypes of the dengue virus: DEN-1, DEN-2, DEN-3, and DEN-4. The chimeric yellow fever dengue tetravalent dengue vaccine (CYD-TDV) is a vaccine currently used in Thailand. This research investigates what the optimal control is when only individuals having documented past dengue infection history are vaccinated. This is the present practice in Thailand and is the latest recommendation of the WHO. The model used is the Susceptible-Infected-Recovered (SIR) model in series configuration for the human population and the Susceptible-Infected (SI) model for the vector population. Both dynamical models for the two populations were recast as optimal control problems with two optimal control parameters. The analysis showed that the equilibrium states were locally asymptotically stable. The numerical solution of the control systems and conclusions are presented.

Epidemiology and challenges of dengue surveillance in the WHO South-East Asia Region

Dengue poses a significant health and economic burden in the WHO South-East Asia Region. Approaches for control need to be aligned with current knowledge on the epidemiology of dengue in the region. Such knowledge will ensure improved targeting of interventions to reduce dengue incidence and its socioeconomic impact. This review was undertaken to describe the contemporary epidemiology of dengue and critically analyse the existing surveillance strategies in the region. Over recent decades, dengue incidence has continued to increase with geographical expansion. The region has now become hyper-endemic for multiple dengue virus serotypes/genotypes. Every epidemic cycle was associated with a change of predominant serotype/genotype and this was often associated with severe disease with intense transmission. Classical larval indices are widely used in vector surveillance and adult mosquito samplings are not implemented as a part of routine surveillance. Further, there is a lack of integration of entomological and disease surveillance systems, often leading to inaction or delays in dengue prevention and control. Disease surveillance does not capture all cases, resulting in under-reporting, and has thus failed to adequately represent the true burden of disease in the region. Possible solutions include incorporating adult mosquito sampling into routine vector surveillance, the establishment of laboratory-based sentinel surveillance, integrated vector and dengue disease surveillance and climate-based early warning systems using available technologies like mobile apps.

A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles

Transmission of dengue fever depends on a complex interplay of human, climate and mosquito dynamics, which often change in time and space. It is well known that its disease dynamics are highly influenced by multiple factors including population susceptibility to infection as well as by microclimates: small-area climatic conditions which create environments favourable for the breeding and survival of mosquitoes. Here, we present a novel machine learning dengue forecasting approach, which, dynamically in time and space, identifies local patterns in weather and population susceptibility to make epidemic predictions at the city level in Brazil, months ahead of the occurrence of disease outbreaks. Weather-based predictions are improved when information on population susceptibility is incorporated, indicating that immunity is an important predictor neglected by most dengue forecast models. Given the generalizability of our methodology to any location or input data, it may prove valuable for public health decision-making aimed at mitigating the effects of seasonal dengue outbreaks in locations globally.

A descriptive analysis of dengue in Peace Corps Volunteers, 2000-2019

BACKGROUND

Peace Corps Volunteers (PCVs) are a unique expatriate population at risk for dengue. Previous studies examined travelers or lacked demographic information about expatriates. We examined dengue incidence among PCVs before and after deployment of an electronic medical record (EMR) to assess temporal and demographic factors.

METHODS

Dengue cases within Peace Corps' Epidemiologic Surveillance System from 2000 to 2019 were identified using a standard case definition, and two timeframes were compared: pre-EMR 2000-2015 and post-EMR 2016-2019.

RESULTS

Annual infections occurred in a roughly 3-year cyclic pattern from 2007 to 2019. Incidence rate decreased from 1.35 cases per 100 dengue Volunteer-years (95% CI 1.28-1.41) in 2000-2015 to 1.25 cases (95% CI 1.10-1.41) in 2016-2019. Among PCVs who served from 2016 to 2019, the majority of infections occurred in females and 20-29 year olds, and 7% were medically evacuated. Among PCVs who served from 2015 to 2019, 21% were hospitalized in-country.

CONCLUSIONS

Among PCVs, a non-significant decrease in dengue incidence occurred from 2000-2015 to 2016-2019. Annual infection rates peaked every three years, offering opportunities for targeted prevention efforts. Dengue infection in PCVs appears to mimic the overall demographic of Peace Corps. Expatriates like PCVs are at an increased risk for dengue infection compared to short-term travelers.

Lying in wait: the resurgence of dengue virus after the Zika epidemic in Brazil

After the Zika virus (ZIKV) epidemic in the Americas in 2016, both Zika and dengue incidence declined to record lows in many countries in 2017–2018, but in 2019 dengue resurged in Brazil, causing ~2.1 million cases. In this study we use epidemiological, climatological and genomic data to investigate dengue dynamics in recent years in Brazil. First, we estimate dengue virus force of infection (FOI) and model mosquito-borne transmission suitability since the early 2000s. Our estimates reveal that DENV transmission was low in 2017–2018, despite conditions being suitable for viral spread. Our study also shows a marked decline in dengue susceptibility between 2002 and 2019, which could explain the synchronous decline of dengue in the country, partially as a result of protective immunity from prior ZIKV and/or DENV infections. Furthermore, we performed phylogeographic analyses using 69 newly sequenced genomes of dengue virus serotype 1 and 2 from Brazil, and found that the outbreaks in 2018–2019 were caused by local DENV lineages that persisted for 5–10 years, circulating cryptically before and after the Zika epidemic. We hypothesize that DENV lineages may circulate at low transmission levels for many years, until local conditions are suitable for higher transmission, when they cause major outbreaks.

Zika and dengue incidence in the Americas declined in 2017–2018, but dengue resurged in 2019 in Brazil. This study uses epidemiological, climatological and genomic data to show that the decline of dengue may be explained by protective immunity from pre-exposure to ZIKV and/or DENV in prior years.

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.

Risk of dengue virus infection according to serostatus in individuals from dengue endemic areas of Mexico

The variability in the host immune response directed against dengue virus (DENV) has demonstrated the need to understand the immune response associated with protection in incident infection. The objective was to estimate the association between serostatus and the risk of incident DENV infection. We used a prospective study from 2014 to 2016 in the localities of Axochiapan and Tepalcingo, Morelos, Mexico. We recruited 966 participants, of which, according to their infection history registered were categorized in four groups. To accomplish the objectives of this study, we selected to 400 participants older than 5 years of age were followed for 2.5 years. Blood samples were taken every 6 months to measure serological status and infection by ELISA. In individuals with at least two previous infections the risk of new infection was lower compared to a seronegative group (hazard ratio adjusted 0.49, 95% CI 0.24-0.98), adjusted for age and locality. Therefore, individuals who have been exposed two times or more to a DENV infection have a lower risk of re-infection, thus showing the role of cross-immunity and its association with protection.

Combine dengue vaccines to optimize effectiveness

Developing a completely effective and safe dengue vaccine has been a complicated process. Dengvaxia®, by Sanofi-Pasteur, and recently TAK003, by Takeda, have strengths and weaknesses, but they seem to complement each other. In this work, we elaborate a rationale that could be applicable in a combined program of these vaccines for the control of dengue.

Multiple arboviral infections during a DENV-2 outbreak in Solomon Islands

Background

Solomon Islands, a country made up of tropical islands, has suffered cyclic dengue fever (DF) outbreaks in the past three decades. An outbreak of dengue-like illness (DLI) that occurred in April 2016 prompted this study, which aimed to determine the population’s immunity status and identify the arboviruses circulating in the country.

Methods

A household survey, involving 188 participants in two urban areas (Honiara and Gizo), and a parallel hospital-based clinical survey were conducted in April 2016. The latter was repeated in December after a surge in DLI cases. Arbovirus IgG ELISA were performed on the household blood samples to determine the prevalence of arboviruses in the community, while qPCR testing of the clinical samples was used to identify the circulating arboviruses. Dengue virus (DENV)-positive samples were further characterized by amplifying and sequencing the envelope gene.

Results

The overall prevalence rates of DENV, Zika virus, and chikungunya virus were 83.4%, 7.6%, and 0.9%, respectively. The qPCR positivity rates of the clinical samples collected in April 2016 were as follows: DENV 39.6%, Zika virus 16.7%, and chikungunya virus 6.3%, which increased to 74%, 48%, and 20% respectively in December 2016. The displacement of the circulating serotype-3, genotype-1, with DENV serotype 2, genotype cosmopolitan was responsible for the outbreak in 2016.

Conclusions

A DENV outbreak in Solomon Islands was caused by the introduction of a single serotype. The high prevalence of DENV provided transient cross-protection, which prevented the introduction of a new serotype from the hyperendemic region for at least 3 years. The severe outcomes seen in the recent outbreak probably resulted from changes in the causative viruses and the effects of population immunity and changes in the outbreak pattern. Solomon Islands needs to step up surveillance to include molecular tools, increase regional communication, and perform timely interventions.

Experiments Investigating the Competitive Growth Advantage of Two Different Genotypes of Human Metapneumovirus: Implications for the Alternation of Genotype Prevalence

Human metapneumovirus (hMPV) is an important pathogen that causes upper and lower respiratory tract infections in children worldwide. hMPV has two major genotypes, hMPV-A and hMPV-B. Epidemiological studies have shown that the two hMPV genotypes alternate in predominance worldwide in recent years. Co-circulation of the two genotypes of hMPV was usually observed and there is no study about the interaction between them, such as competitive replication, which maybe the possible mechanisms for alternating prevalence of subtypes. Our present study have used two different genotypes of hMPV (genotype A: NL/1/00; B: NL/1/99) in different proportions in animal model (BALB/c mice) and cell model (Vero-E6) separately. The result showed that the competitive growth does exist in BALB/c mice, genotype B had a strong competitive advantage. However, genotype B did not cause more severe disease than non-predominant (genotype A) or mixed strains in the study, which were evaluated by the body weight, airway hyperresponsiveness and lung pathology of mouse. In cell model, competitive growth and the two genotypes alternately prevalence were observed. In summary, we confirmed that there was a competitive replication between hMPV genotype A and B, and no difference in disease severity caused by the two subtypes. This study shows a new insight to understand the alternation of hMPV genotype prevalence through genotype competition and provide experimental evidence for disease control and vaccine design.

Considering Genomic and Immunological Correlates of Protection for a Dengue Intervention

Over three billion are at risk of dengue infection with more than 100 million a year presenting with symptoms that can lead to deadly haemorrhagic disease. There are however no treatments available and the only licensed vaccine shows limited efficacy and is able to enhance the disease in some cases. These failures have mainly been due to the complex pathology and lack of understanding of the correlates of protection for dengue virus (DENV) infection. With increasing data suggesting both a protective and detrimental effect for antibodies and CD8 T-cells whilst having complex environmental dynamics. This review discusses the roles of genomic and immunological aspects of DENV infection, providing both a historical interpretation and fresh discussion on how this information can be used for the next generation of dengue interventions.

An open challenge to advance probabilistic forecasting for dengue epidemics

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.

Considerations for the 2030 Sustainable Development Goals for dengue

Dengue circulates endemically in many tropical and subtropical regions. In 2012, the World Health Organization (WHO) set out goals to reduce dengue mortality and morbidity by 50% and 25%, respectively, between 2010 and 2020. These goals will not be met. This is, in part, due to existing interventions being insufficiently effective to prevent spread. Further, complex and variable patterns of disease presentation coupled with imperfect surveillance systems mean that even tracking changes in burden is rarely possible. As part of the Sustainable Development Goals, WHO will propose new dengue-specific goals for 2030. The 2030 goals provide an opportunity for focused action on tackling dengue burden but should be carefully developed to be ambitious but also technically feasible. Here we discuss the potential for clearly defined case fatality rates and the rollout of new and effective intervention technologies to form the foundation of these future goals. Further, we highlight how the complexity of dengue epidemiology limits the feasibility of goals that instead target dengue outbreaks.

Dengue in Santander State, Colombia: fluctuations in the prevalence of virus serotypes are linked to dengue incidence and genetic diversity of the circulating viruses

OBJECTIVE

To investigate the link between fluctuations in the prevalence of dengue virus (DENV) serotypes and the number of dengue cases in the metropolitan area of Bucaramanga, Santander State, Colombia, in the 2007-2010 and 2014-2017 periods.

METHOD

Viruses were isolated from febrile patient samples by direct application to C6/36-HT cells and typed using monoclonal antibodies. We performed autocorrelation and cross-correlation analyses to determine whether fluctuations in the prevalence of DENV serotypes and dengue cases were correlated. Full envelope (E) gene sequences were employed to examine the genetic diversity of serotypes circulating by using a phylogenetic approach.

RESULTS

All four dengue virus serotypes were detected. DENV-1 was the dominant serotype in both periods followed by DENV-3 or DENV-2 depending on the period; DENV-4 was the least prevalent virus in both periods. Cross-correlation analyses suggest a temporal relation between the fluctuations in the prevalence of DENV serotypes, which were almost simultaneous (lag = 0) or related to recent past fluctuations (lag > 1.0) in the number of dengue cases. Data suggest that a sustained predominance of DENV-1, an increase of the DENV-4 prevalence, and a switch from DENV-3 to DENV-2 could be linked to an outbreak. Circulating viruses were grouped into Genotype V, Asia/American III and II for DENV-1, -2, -3 and -4, respectively; intragenotypic diversity was detected.

CONCLUSIONS

The present work highlights the need of comprehensive studies on dynamics of DENV in Colombia to understand transmission of dengue and evaluate the effectiveness of a vaccination programme.

Dengue viral infection in Indonesia: Epidemiology, diagnostic challenges, and mutations from an observational cohort study

BACKGROUND

Dengue virus (DENV) infection is a major cause of acute febrile illness in Indonesia. Diagnostic inaccuracy may occur due to its varied and non-specific presentation. Characterization of DENV epidemiology, clinical presentation, and virology will facilitate appropriate clinical management and public health policy.

METHODOLOGY/PRINCIPAL FINDINGS

A multicenter observational cohort study was conducted in Indonesia to assess causes of acute fever requiring hospitalization. Clinical information and specimens were collected at enrollment, 14-28 days, and 3 months from 1,486 children and adults. Total of 468 (31.9%) cases of DENV infection were confirmed by reference laboratory assays. Of these, 414 (88.5%) were accurately diagnosed and 54 had been misdiagnosed as another infection by sites. One hundred initially suspected dengue cases were finally classified as 'non-dengue'; other pathogens were identified in 58 of those cases. Mortality of DENV infection was low (0.6%). Prior DENV exposure was found in 92.3% of subjects >12 years. DENV circulated year-round in all cities, with higher incidence from January to March. DENV-3 and DENV-1 were the predominant serotypes. This study identified DENV-1 with TS119(C→T) substitution in the serotyping primer annealing site, leading to failure of serotype determination.

CONCLUSIONS/SIGNIFICANCE

DENV is a common etiology of acute febrile illness requiring hospitalization in Indonesia. Diagnostic accuracy at clinical sites merits optimization since misdiagnosis of DENV infection and over-estimation of dengue can negatively impact management and outcomes. Mutation at the annealing site of the serotyping primer may confound diagnosis. Clinicians should consider following diagnostic algorithms that include DENV confirmatory testing. Policy-makers should prioritize development of laboratory capacity for diagnosis of DENV.

A vector-host model to assess the impact of superinfection exclusion on vaccination strategies using dengue and yellow fever as case studies

Superinfection exclusion is a phenomenon whereby the co-infection of a host with a secondary pathogen is prevented due to a current infection by another closely-related pathogenic strain. We construct a novel vector-host mathematical model for two pathogens that exhibit superinfection exclusion and simultaneously account for vaccination strategies against them. We then derive the conditions under which an endemic disease will prevent the establishment of another through the action of superinfection exclusion and show that vaccination against the endemic strain can enable the previously suppressed strain to invade the population. Through appropriate parameterisation of the model for dengue and yellow fever we find that superinfection exclusion alone is unlikely to explain the absence of yellow fever in many regions where dengue is endemic, and that the rollout of the recently licensed dengue vaccine, Dengvaxia, is unlikely to enable the establishment of Yellow Fever in regions where it has previously been absent.

Cross-serotype interactions and disease outcome prediction of dengue infections in Vietnam

Dengue pathogenesis is extremely complex. Dengue infections are thought to induce life-long immunity from homologous challenges as well as a multi-factorial heterologous risk enhancement. Here, we use the data collected from a prospective cohort study of dengue infections in schoolchildren in Vietnam to disentangle how serotype interactions modulate clinical disease risk in the year following serum collection. We use multinomial logistic regression to correlate the yearly neutralizing antibody measurements obtained with each infecting serotype in all dengue clinical cases collected over the course of 6 years (2004–2009). This allowed us to extrapolate a fully discretised matrix of serotype interactions, revealing clear signals of increased risk of clinical illness in individuals primed with a previous dengue infection. The sequences of infections which produced a higher risk of dengue fever upon secondary infection are: DEN1 followed by DEN2; DEN1 followed by DEN4; DEN2 followed by DEN3; and DEN4 followed by DEN3. We also used this longitudinal data to train a machine learning algorithm on antibody titre differences between consecutive years to unveil asymptomatic dengue infections and estimate asymptomatic infection to clinical case ratios over time, allowing for a better characterisation of the population’s past exposure to different serotypes.

The Dengue ED3 Dot Assay, a Novel Serological Test for the Detection of Denguevirus Type-Specific Antibodies and Its Application in a Retrospective Seroprevalence Study

There are four distinct antigenic serotypes of dengue viruses (DENV-1-4). Sequential infections with different serotypes lead to cross-reactive but also serotype-specific neutralizing antibody responses. Neutralization assays are considered as gold standard for serotype-specific antibody detection. However, for retrospective seroprevalence studies, access to large serum quantities is limited making neutralization assays well-nigh impossible. Therefore, a serological test, wasting only 10 µL serum, was developed using fusion proteins of maltose binding protein and E protein domain 3 (MBP-ED3) as antigens. Twelve MBP-ED3 antigens for DENV-1-4, three MBP-ED3 antigens for WNV, JEV, and TBEV, and MBP were dotted onto a single nitrocellulose strip. ED3 dot assay results were compared to virus neutralization and ED3 ELISA test results, showing a >90% accordance for DENV-1 and a 100% accordance for DENV-2, making the test specifically useful for DENV-1/-2 serotype-specific antibody detection. Since 2010, DENV-1 has replaced DENV-2 as the dominant serotype in Cambodia. In a retrospective cohort analysis, sera collected during the DENV-1/-2 endemic period showed a shift to DENV-2-specific antibody responses in 2012 paralleled by the decline of DENV-2 infections. Altogether, the ED3 dot assay is a serum-, time- and money-saving diagnostic tool for serotype-specific antibody detection, especially when serum samples are limited.

Prediction of dengue outbreaks based on disease surveillance, meteorological and socio-economic data

Background

The goal of this research is to create a system that can use the available relevant information about the factors responsible for the spread of dengue and; use it to predict the occurrence of dengue within a geographical region, so that public health experts can prepare for, manage and control the epidemic. Our study presents new geospatial insights into our understanding and management of health, disease and health-care systems.

Methods

We present a machine learning-based methodology capable of providing forecast estimates of dengue prediction in each of the fifty districts of Thailand by leveraging data from multiple data sources. Using a set of prediction variables, we show an increase in prediction accuracy of the model with an optimal combination of predictors which include: meteorological data, clinical data, lag variables of disease surveillance, socioeconomic data and the data encoding spatial dependence on dengue transmission. We use Generalized Additive Models (GAMs) to fit the relationships between the predictors (with a lag of one month) and the clinical data of Dengue hemorrhagic fever (DHF) using the data from 2008 to 2012. Using the data from 2013 to 2015 and a comparative set of prediction models, we evaluate the predictive ability of the fitted models according to RMSE and SRMSE as well as using adjusted R-squared value, deviance explained and change in AIC.

Results

The model allows for combining different predictors to make forecasts with a lead time of one month and also describe the statistical significance of the variables used to characterize the forecast. The discriminating ability of the final model was evaluated against Bangkok specific constant threshold and WHO moving threshold of the epidemic in terms of specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV).

Conclusions

The out-of-sample validation showed poorer results than the in-sample validation, however it demonstrated ability in detecting outbreaks up-to one month ahead. We also determine that for the predicting dengue outbreaks within a district, the influence of dengue incidences and socioeconomic data from the surrounding districts is statistically significant. This validates the influence of movement patterns of people and spatial heterogeneity of human activities on the spread of the epidemic.