Dengue Virus Transmission Dynamics Research Articles

Insight into the seroepidemiology and dynamics of circulating serotypes of dengue virus over a 4 year period in western Uttar Pradesh, India.

An important public health problem in India is dengue infection, with every year seeing an increase in cases of dengue fever. Dengue affects all individuals irrespective of their gender and age, although the infection rate is higher among males and younger people. Despite low severity in general, dengue virus can cause severe health conditions in some individuals. Genetic characterization of circulating endemic dengue virus (DENV) serotypes plays a significant role in providing epidemiological knowledge and subsequent vaccine development. In the present study, over a 4 year period, we assessed DENV transmission dynamics in major regions of western Uttar Pradesh in North India. ELISA tests were used to diagnose dengue, and PCRs were used to determine the circulating serotype. We found that dengue infection peaks after the rainy season and affects all sexes and ages. A total of 1277 individuals were found positive for dengue; among them, 61.7 % were male and 38.3 % were female. DEN-1 was found in 23.12 %, DEN-2 in 45 %, DEN-3 in 29.06 % and DEN-4 in 1.5 % of the dengue-infected individuals. All four DENV serotypes were circulating in the study area, and DENV serotype-2 (DEN-2) was the most prevalent serotype.

Dengue incidence and length of viremia by RT-PCR in a prospective observational community contact cluster study from 2005-2009 in Indonesia.

Dengue has become a major global health threat since being recognized three centuries ago. Important gaps remain in understanding the transmission dynamics of dengue virus (DENV) infection. This study reports the results of a prospective observational cluster study that investigated the incidence of symptomatic and asymptomatic infections and length of viremia among close community contacts of hospitalized DENV-infected patients. Between 2005 and 2009, dengue-confirmed cases (n = 97) admitted to Hasan Sadikin Hospital in Bandung, Indonesia, were enrolled as index cases. Subsequently, twenty close community contacts (n = 1928) living with and around the index cases were included and followed up for up to 14 days. Body temperature was measured daily; blood samples were collected every 3-4 days and when reported fever. DENV infection was confirmed using Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR), IgM rapid test, and Enzyme-linked Immunosorbent Assay (ELISA). Among the 1928 community contacts, a total of 72 (3.7%) acute DENV infections were diagnosed, which equates to an incidence of 636 cases per 1,000 person-years (95% Confidence interval (CI) 588 to 687 cases per 1,000 person-years). Twenty-nine cases (40%) were symptomatic (22 dengue fever (DF) & 7 dengue hemorrhagic fever (DHF)), and 43 (60%) were asymptomatic. Primary and secondary DENV infections were detected in 18 (25%) and 54 (75%) subjects. Among the RT-PCR positives, viremia was observed as early as seven days before fever onset and converted to negative as late as seven days after the onset of fever. DENV infections are common among close community contacts of hospitalized dengue patients. The high number of asymptomatic infections and the observation that viremia precedes the onset of fever for up to seven days highlight the importance of unrecognized dengue transmission and the need for improved transmission control.

Quantifying heterogeneities in arbovirus transmission: Description of the rationale and methodology for a prospective longitudinal study of dengue and Zika virus transmission in Iquitos, Peru (2014-2019).

Current knowledge of dengue virus (DENV) transmission provides only a partial understanding of a complex and dynamic system yielding a public health track record that has more failures than successes. An important part of the problem is that the foundation for contemporary interventions includes a series of longstanding, but untested, assumptions based on a relatively small portion of the human population; i.e., people who are convenient to study because they manifest clinically apparent disease. Approaching dengue from the perspective of people with overt illness has produced an extensive body of useful literature. It has not, however, fully embraced heterogeneities in virus transmission dynamics that are increasingly recognized as key information still missing in the struggle to control the most important insect-transmitted viral infection of humans. Only in the last 20 years have there been significant efforts to carry out comprehensive longitudinal dengue studies. This manuscript provides the rationale and comprehensive, integrated description of the methodology for a five-year longitudinal cohort study based in the tropical city of Iquitos, in the heart of the Peruvian Amazon. Primary data collection for this study was completed in 2019. Although some manuscripts have been published to date, our principal objective here is to support subsequent publications by describing in detail the structure, methodology, and significance of a specific research program. Our project was designed to study people across the entire continuum of disease, with the ultimate goal of quantifying heterogeneities in human variables that affect DENV transmission dynamics and prevention. Because our study design is applicable to other Aedes transmitted viruses, we used it to gain insights into Zika virus (ZIKV) transmission when during the project period ZIKV was introduced and circulated in Iquitos. Our prospective contact cluster investigation design was initiated by detecttion of a person with a symptomatic DENV infection and then followed that person's immediate contacts. This allowed us to monitor individuals at high risk of DENV infection, including people with clinically inapparent and mild infections that are otherwise difficult to detect. We aimed to fill knowledge gaps by defining the contribution to DENV transmission dynamics of (1) the understudied majority of DENV-infected people with inapparent and mild infections and (2) epidemiological, entomological, and socio-behavioral sources of heterogeneity. By accounting for factors underlying variation in each person's contribution to transmission we sought to better determine the type and extent of effort needed to better prevent virus transmission and disease.

Analysis of Vector-host SEIR-SEI Dengue Epidemiological Model

Approximately worldwide 50 nations are still infected with the deadly dengue virus. This mosquito-borne illness spreads rapidly. Epidemiological models can provide fundamental recommendations for public health professionals, allowing them to analyze variables impacting disease prevention and control efforts. In this paper, we present a host-vector mathematical model that depicts the Dengue virus transmission dynamics utilizing a susceptible-exposed-infected-recovered (SEIR) model for the human interacting with a susceptible-exposed-infected (SEI) model for the mosquito. Using the Next Generation Technique, the basic reproduction number of the model is calculated. The local stability shows that if R0<1 the system is asymptotically stable and the disease dies out, otherwise unstable. The Lyapunov function is also used to evaluate the global stability of disease-free and endemic equilibrium points. To analyze the effect of the crucial aspects of the disease's transmission and to validate the analytical findings, numerical simulations of a variety of compartments have been constructed using MATLAB. The sensitivity analysis of the epidemic model is performed to establish the relative significance of the model parameters to disease transmission.

Modeling optimal vaccination strategy for dengue epidemic model: a case study of India

Dengue fever is a mosquito-borne infectious disease which is transmitted through Aedes aegypti mosquitoes. It is one of the major global health issues in the tropical and subtropical regions of the world. Its dynamics are very complicated owing to the coupling among multiple transmission pathways and various components in pathogen. Due to absence of proper medicine or vaccination, mathematical modeling plays an important role in understanding the disease dynamics and in designing strategies to control the spread of dengue virus. In this paper, we studied a non-linear vector-host model to investigate the transmission dynamics of dengue virus which can be controlled by vaccination as well as treatment. Analysis of model start with the basic reproduction number , when it is less than one, the system become locally asymptotically stable about the virus-free equilibrium point. We calibrated our proposed model corresponding to transmission of dengue virus using real data for six Indian states, namely Tamil Nadu, Kerala, Delhi, Gujarat, Rajasthan and Karnataka by using the least square method. Moreover, we performed normalized forward sensitivity analysis of the basic reproduction number and obtained that mitigating the disease transmission rate of mosquito and human population is the most important factor in achieving dengue control. Finally, an objective functional has been developed to minimize the cost of the vaccination and solved with the aid of the Pontryagin’s Maximum Principle. The implementation of the optimal treatment policy shows a significant reduction of the hospitalized individuals as well as infected individuals. We then performed extensive numerical simulations to validate our theoretical analysis with aid of the estimated model parameters.

Dengue virus seroprevalence study in Bangphae district, Ratchaburi, Thailand: A cohort study in 2012-2015.

BackgroundTo determine the seroprevalence and transmission dynamics of dengue virus (DENV), age-stratified longitudinal serological surveys were conducted in Bangphae district, Ratchaburi province, Thailand, for 3 years between April 2012 and April 2015.MethodologyThe surveys enrolled 2012 healthy children and adults between 1 and 55 years-of-age, and a longitudinal serosurvey of six repeated bleeds of the same cohort of individuals was conducted every 8 months for the first 2 years (M0, M8, M16) and every half a year (M24, M30, M36) for the rest of the study period. All samples were tested using in-house indirect sandwich dengue IgG ELISA to determine DENV antibody titer, and 640 paired samples which showed rising of DENV IgG titers in paired serum were further tested using in-house neutralization assay, Plaque Reduction Neutralization Test (PRNT50).Principal findingsWhen compared against the gold standard based on the results of PRNT50, sensitivity and specificity of indirect ELISA were found to be both about 85%. The overall DENV IgG positivity determined by ELISA was 74.3% in 2012 and increased to 79.4% by the final sample collection in 2015. In our study sample, more than 98% of subjects older than 25 years were found to be seropositive. Among 518 IgG negative subjects at enrollment, the seroconversion rates were measured in paired bleeds; the rates (between successive visits, approximately 6 months) ranged between 4.8% (between M16 and M24) and 14.7% (between M0 and M8). The dominant serotype of primary DENV infection cases based on seroconversion was identified from the PRNT results and it was DENV-2.ConclusionsOur study documented high levels of seroprevalence and rate of transmission. Given the importance of the serostatus and disease burden in consideration for dengue vaccine introduction, our data could be used in decision-making on implementation of various dengue control and preventive measures.

A Framework for Weather-Driven Dengue Virus Transmission Dynamics in Different Brazilian Regions.

This study investigated a model to assess the role of climate fluctuations on dengue (DENV) dynamics from 2010 to 2019 in four Brazilian municipalities. The proposed transmission model was based on a preexisting SEI-SIR model, but also incorporates the vector vertical transmission and the vector’s egg compartment, thus allowing rainfall to be introduced to modulate egg-hatching. Temperature and rainfall satellite data throughout the decade were used as climatic model inputs. A sensitivity analysis was performed to understand the role of each parameter. The model-simulated scenario was compared to the observed dengue incidence and the findings indicate that the model was able to capture the observed seasonal dengue incidence pattern with good accuracy until 2016, although higher deviations were observed from 2016 to 2019. The results further demonstrate that vertical transmission fluctuations can affect attack transmission rates and patterns, suggesting the need to investigate the contribution of vertical transmission to dengue transmission dynamics in future assessments. The improved understanding of the relationship between different environment variables and dengue transmission achieved by the proposed model can contribute to public health policies regarding mosquito-borne diseases.

The evolution of dengue-2 viruses in Malindi, Kenya and greater East Africa: Epidemiological and immunological implications.

Kenya experiences a substantial burden of dengue, yet there are very few DENV-2 sequence data available from this country and indeed the entire continent of Africa. We therefore undertook whole genome sequencing and evolutionary analysis of fourteen dengue virus (DENV)-2 strains sampled from Malindi sub-County Hospital during the 2017 DENV-2 outbreak in the Kenyan coast. We further performed an extended East African phylogenetic analysis, which leveraged 26 complete African env genes. Maximum likelihood analysis showed that the 2017 outbreak was due to the Cosmopolitan genotype, indicating that this has been the only confirmed human DENV-2 genotype circulating in Africa to date. Phylogeographic analyses indicated transmission of DENV-2 viruses between East Africa and South/South-West Asia. Time-scaled genealogies show that DENV-2 viruses shows spatial structure at the country level in Kenya, with a time-to-most-common-recent ancestor analysis indicating that these DENV-2 strains were circulating for up to 5.38 years in Kenya before detection in the 2017 Malindi outbreak. Selection pressure analyses indicated sampled Kenyan DENV strains uniquely being under positive selection at 6 sites, predominantly across the non-structural genes, and epitope prediction analyses showed that one of these sites corresponds to a putative predicted MHC-I CD8+ DENV-2 Cosmopolitan virus epitope only evident in a sampled Kenyan virus. Taken together, our findings indicate that the 2017 Malindi DENV-2 outbreak arose from a strain which had circulated for several years in Kenya before recent detection, has experienced diversifying selection pressure, and may contain new putative immunogens relevant to vaccine design. These findings prompt further genomic epidemiology studies in this and other Kenyan locations to further elucidate the transmission dynamics of DENV in this region.

Vaccination and vector control effect on dengue virus transmission dynamics: Modelling and simulation

Abstract This paper presents a two-strain compartmental dengue model with variable humans and mosquitoes populations sizes. The model incorporates two control measures: Dengvaxia vaccine and insecticide (adulticide) to forecast the transmission and effective control strategy for dengue in Madeira Island if there is a new outbreak with a different virus serotype after the first outbreak in 2012. The basic reproduction number, R 0 = max { R 01 , R 0 j } , associated with the model is computed using the next generation matrix operator. The disease-free equilibrium is found to be locally asymptotically stable when both R 01 , R 0 j 1 , but unstable otherwise. The global asymptotic stability of the model is derived using the comparison theorem. Sensitivity analysis is carried out on the model parameters. The results of the analysis show that mosquito biting and death rates are the most sensitive parameters. Three strategies: the use of Dengvaxia vaccine only, the use of adulticide only, and the combination of Dengvaxia vaccine and adulticide, are considered for the control implementation under two scenarios (less and more aggressive cases). The numerical results show that a strategy which is based on Dengvaxia vaccine and adulticide is the most effective strategy for controlling dengue disease transmission in both scenarios among the considered strategies.

Modeling the effect of temperature on dengue virus transmission with periodic delay differential equations

Dengue fever is a re-emergent mosquito-borne disease, which prevails in tropical and subtropical regions, mainly in urban and peri-urban areas. Its incidence has increased fourfold since 1970, and dengue fever has become the most prevalent mosquito-borne disease in humans now. In order to study the effect of temperature on the dengue virus transmission, we formulate a dengue virus transmission model with maturation delay for mosquito production and seasonality. The basic reproduction number $\mathbb{R}_0$ of the model is computed, and results suggest that the dengue fever will die out if $\mathbb{R}_0$ < 1, and there exists at least one positive periodic solution and the disease will persist if $\mathbb{R}_0$ > 1. Theoretical results are applied to the outbreak of dengue fever in Guangdong province, China. Simulations reveal that the temperature change causes the periodic oscillations of dengue fever cases, which is good accordance with the reported cases of dengue fever in Guangdong province. Our study contributes to a better understanding of dengue virus transmission dynamics and proves beneficial in preventing and controlling of dengue fever.

Dengue illness impacts daily human mobility patterns in Iquitos, Peru

BackgroundHuman mobility plays a central role in shaping pathogen transmission by generating spatial and/or individual variability in potential pathogen-transmitting contacts. Recent research has shown that symptomatic infection can influence human mobility and pathogen transmission dynamics. Better understanding the complex relationship between symptom severity, infectiousness, and human mobility requires quantification of movement patterns throughout infectiousness. For dengue virus (DENV), human infectiousness peaks 0–2 days after symptom onset, making it paramount to understand human movement patterns from the beginning of illness.Methodology and principal findingsThrough community-based febrile surveillance and RT-PCR assays, we identified a cohort of DENV+ residents of the city of Iquitos, Peru (n = 63). Using retrospective interviews, we measured the movements of these individuals when healthy and during each day of symptomatic illness. The most dramatic changes in mobility occurred during the first three days after symptom onset; individuals visited significantly fewer locations (Wilcoxon test, p = 0.017) and spent significantly more time at home (Wilcoxon test, p = 0.005), compared to when healthy. By 7–9 days after symptom onset, mobility measures had returned to healthy levels. Throughout an individual’s symptomatic period, the day of illness and their subjective sense of well-being were the most significant predictors for the number of locations and houses they visited.Conclusions/SignificanceOur study is one of the first to collect and analyze human mobility data at a daily scale during symptomatic infection. Accounting for the observed changes in human mobility throughout illness will improve understanding of the impact of disease on DENV transmission dynamics and the interpretation of public health-based surveillance data.

Intra-epidemic evolutionary dynamics of a Dengue virus type 1 population reveal mutant spectra that correlate with disease transmission.

Dengue virus (DENV) is currently the most prevalent mosquito-borne viral pathogen. DENVs naturally exist as highly heterogeneous populations. Even though the descriptions on DENV diversity are plentiful, only a few studies have narrated the dynamics of intra-epidemic virus diversity at a fine scale. Such accounts are important to decipher the reciprocal relationship between viral evolutionary dynamics and disease transmission that shape dengue epidemiology. In the current study, we present a micro-scale genetic analysis of a monophyletic lineage of DENV-1 genotype III (epidemic lineage) detected from November 2012 to May 2014. The lineage was involved in an unprecedented dengue epidemic in Singapore during 2013–2014. Our findings showed that the epidemic lineage was an ensemble of mutants (variants) originated from an initial mixed viral population. The composition of mutant spectrum was dynamic and positively correlated with case load. The close interaction between viral evolution and transmission intensity indicated that tracking genetic diversity through time is potentially a useful tool to infer DENV transmission dynamics and thereby, to assess the epidemic risk in a disease control perspective. Moreover, such information is salient to understand the viral basis of clinical outcome and immune response variations that is imperative to effective vaccine design.

Time-varying, serotype-specific force of infection of dengue virus.

Infectious disease models play a key role in public health planning. These models rely on accurate estimates of key transmission parameters such as the force of infection (FoI), which is the per-capita risk of a susceptible person being infected. The FoI captures the fundamental dynamics of transmission and is crucial for gauging control efforts, such as identifying vaccination targets. Dengue virus (DENV) is a mosquito-borne, multiserotype pathogen that currently infects ∼390 million people a year. Existing estimates of the DENV FoI are inaccurate because they rely on the unrealistic assumption that risk is constant over time. Dengue models are thus unreliable for designing vaccine deployment strategies. Here, we present to our knowledge the first time-varying (daily), serotype-specific estimates of DENV FoIs using a spline-based fitting procedure designed to examine a 12-y, longitudinal DENV serological dataset from Iquitos, Peru (11,703 individuals, 38,416 samples, and 22,301 serotype-specific DENV infections from 1999 to 2010). The yearly DENV FoI varied markedly across time and serotypes (0-0.33), as did daily basic reproductive numbers (0.49-4.72). During specific time periods, the FoI fluctuations correlated across serotypes, indicating that different DENV serotypes shared common transmission drivers. The marked variation in transmission intensity that we detected indicates that intervention targets based on one-time estimates of the FoI could underestimate the level of effort needed to prevent disease. Our description of dengue virus transmission dynamics is unprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs.

Reduced Risk of Disease During Postsecondary Dengue Virus Infections

Antibodies induced by infection with any 1 of 4 dengue virus (DENV) serotypes (DENV-1-4) may influence the clinical outcome of subsequent heterologous infections. To quantify potential cross-protective effects, we estimated disease risk as a function of DENV infection, using data from longitudinal studies performed from September 2006 through February 2011 in Iquitos, Peru, during periods of DENV-3 and DENV-4 transmission. DENV infections before and during the study period were determined by analysis of serial serum samples with virus neutralization tests. Third and fourth infections were classified as postsecondary infections. Dengue fever cases were detected by door-to-door surveillance for acute febrile illness. Among susceptible participants, 39% (420/1077) and 53% (1595/2997) seroconverted to DENV-3 and DENV-4, respectively. Disease was detected in 7% of DENV-3 infections and 10% of DENV-4 infections. Disease during postsecondary infections was reduced by 93% for DENV-3 and 64% for DENV-4, compared with primary and secondary infections. Despite lower disease rates, postsecondary infections constituted a significant proportion of apparent infections (14% [for DENV-3 infections], 45% [for DENV-4 infections]). Preexisting heterotypic antibodies markedly reduced but did not eliminate the risk of disease in this study population. These results improve understanding of how preinfection history can be associated with dengue outcomes and DENV transmission dynamics.

Reduction of Aedes aegypti Vector Competence for Dengue Virus under Large Temperature Fluctuations

Diurnal temperature fluctuations can fundamentally alter mosquito biology and mosquito-virus interactions in ways that impact pathogen transmission. We investigated the effect of two daily fluctuating temperature profiles on Aedes aegypti vector competence for dengue virus (DENV) serotype-1. A large diurnal temperature range of 18.6°C around a 26°C mean, corresponding with the low DENV transmission season in northwestern Thailand, reduced midgut infection rates and tended to extend the virus extrinsic incubation period. Dissemination was first observed at day 7 under small fluctuations (7.6°C; corresponding with high DENV transmission) and constant control temperature, but not until Day 11 for the large diurnal temperature range. Results indicate that female Ae. aegypti in northwest Thailand are less likely to transmit DENV during the low than high transmission season because of reduced DENV susceptibility and extended virus extrinsic incubation period. Better understanding of DENV transmission dynamics will come with improved knowledge of temperature effects on mosquito-virus interactions.

Space‐time analysis of hospitalised dengue patients in rural Thailand reveals important temporal intervals in the pattern of dengue virus transmission

To determine the temporal intervals at which spatial clustering of dengue hospitalisations occurs. Space-time analysis of 262 people hospitalised and serologically confirmed with dengue virus infections in Kamphaeng Phet, Thailand was performed. The cases were observed between 1 January 2009 and 6 May 2011. Spatial coordinates of each patient's home were captured using the Global Positioning System. A novel method based on the Knox test was used to determine the temporal intervals between cases at which spatial clustering occurred. These intervals are indicative of the length of time between successive illnesses in the chain of dengue virus transmission. The strongest spatial clustering occurred at the 15-17-day interval. There was also significant spatial clustering over short intervals (2-5 days). The highest excess risk was observed within 200 m of a previous hospitalised case and significantly elevated risk persisted within this distance for 32-34 days. Fifteen to seventeen days are the most likely serial interval between successive dengue illnesses. This novel method relies only on passively detected, hospitalised case data with household locations and provides a useful tool for understanding region-specific and outbreak-specific dengue virus transmission dynamics.

Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti

Most studies on the ability of insect populations to transmit pathogens consider only constant temperatures and do not account for realistic daily temperature fluctuations that can impact vector-pathogen interactions. Here, we show that diurnal temperature range (DTR) affects two important parameters underlying dengue virus (DENV) transmission by Aedes aegypti. In two independent experiments using different DENV serotypes, mosquitoes were less susceptible to virus infection and died faster under larger DTR around the same mean temperature. Large DTR (20 °C) decreased the probability of midgut infection, but not duration of the virus extrinsic incubation period (EIP), compared with moderate DTR (10 °C) or constant temperature. A thermodynamic model predicted that at mean temperatures <18 °C, DENV transmission increases as DTR increases, whereas at mean temperatures >18 °C, larger DTR reduces DENV transmission. The negative impact of DTR on Ae. aegypti survival indicates that large temperature fluctuations will reduce the probability of vector survival through EIP and expectation of infectious life. Seasonal variation in the amplitude of daily temperature fluctuations helps to explain seasonal forcing of DENV transmission at locations where average temperature does not vary seasonally and mosquito abundance is not associated with dengue incidence. Mosquitoes lived longer and were more likely to become infected under moderate temperature fluctuations, which is typical of the high DENV transmission season than under large temperature fluctuations, which is typical of the low DENV transmission season. Our findings reveal the importance of considering short-term temperature variations when studying DENV transmission dynamics.

Proactive Vector Control Strategies and Improved Monitoring and Evaluation Practices for Dengue Prevention

Despite tremendous efforts by public health organizations in dengue-endemic countries, it has proven difficult to achieve effective and sustainable control of the primary dengue virus vector Aedes aegypti (L.) and to effectively disrupt dengue outbreaks. This problem has multiple root causes, including uncontrolled urbanization, increased global spread of dengue viruses, and vector and dengue control programs not being provided adequate resources. In this forum article, we give an overview of the basic elements of a vector and dengue control program and describe a continuous improvement cyclical model to systematically and incrementally improve control program performance by regular efforts to identify ineffective methods and inferior technology, and then replacing them with better performing alternatives. The first step includes assessments of the overall resource allocation among vector/dengue control program activities, the efficacy of currently used vector control methods, and the appropriateness of technology used to support the program. We expect this will reveal that 1) some currently used vector control methods are not effective, 2) resource allocations often are skewed toward reactive vector control measures, and 3) proactive approaches commonly are underfunded and therefore poorly executed. Next steps are to conceptualize desired changes to vector control methods or technologies used and then to operationally determine in pilot studies whether these changes are likely to improve control program performance. This should be followed by a shift in resource allocation to replace ineffective methods and inferior technology with more effective and operationally tested alternatives. The cyclical and self-improving nature of the continuous improvement model will produce locally appropriate management strategies that continually are adapted to counter changes in vector population or dengue virus transmission dynamics. We discuss promising proactive vector control approaches and the continued need for the vector and dengue control community to incorporate emerging technologies and to partner with academia, business and the community-at-large to identify new solutions that reduce dengue.