House-to-house human movement drives dengue virus transmission

Effects of ambient temperature and precipitation on the risk of dengue fever: A systematic review and updated meta-analysis

OBJECTIVES

We systematically reviewed the published studies on the relationship between dengue fever and meteorological factors and applied a meta-analysis to explore the effects of ambient temperature and precipitation on dengue fever.

METHODS

We completed the literature search by the end of September 1st, 2019 using databases including Science Direct, PubMed, Web of Science, and Google Scholar. We extracted relative risks (RRs) in selected studies and converted all effect estimates to the RRs per 1 °C increase in temperature and 10 mm increase in precipitation, and combined all standardized RRs together using random-effect meta-analysis.

RESULTS

Our results show that dengue fever was significantly associated with both temperature and precipitation. Our subgroup analyses suggested that the effect of temperature on dengue fever was most pronounced in high-income subtropical areas. The pooled RR of dengue fever associated with the maximum temperature was much lower than the overall effect.

CONCLUSIONS

Temperature and precipitation are important risk factors for dengue fever. Future studies should focus on factors that can distort the effects of temperature and precipitation.

The Absence of Yellow Fever in Asia: History, Hypotheses, Vector Dispersal, Possibility of YF in Asia, and Other Enigmas

Since the recent epidemics of yellow fever in Angola and Brazil as well as the importation of cases to China in 2016, there has been an increased interest in the century-old enigma, absence of yellow fever in Asia. Although this topic has been repeatedly reviewed before, the history of human intervention has never been considered a critical factor. A two-stage literature search online for this review, however, yielded a rich history indispensable for the debate over this medical enigma. As we combat the pandemic of COVID-19 coronavirus worldwide today, we can learn invaluable lessons from the historical events in Asia. In this review, I explore the history first and then critically examine in depth major hypotheses proposed in light of accumulated data, global dispersal of the principal vector, patterns of YF transmission, persistence of urban transmission, and the possibility of YF in Asia. Through this process of re-examination of the current knowledge, the subjects for research that should be conducted are identified. This review also reveals the importance of holistic approach incorporating ecological and human factors for many unresolved subjects, such as the enigma of YF absence in Asia, vector competence, vector dispersal, spillback, viral persistence and transmission mechanisms.

Surveillance of dengue virus in individual Aedes aegypti mosquitoes collected concurrently with suspected human cases in Tarlac City, Philippines

BACKGROUND

Vector control measures are critical for the prevention and reduction of dengue virus (DENV) transmission. Effective vector control is reliant not only on knowledge of mosquito abundance, but also on the timely and accurate detection of mosquito-borne infection. Mosquito-based virus surveillance programs typically rely on pool-based mosquito testing, although whether individual-based mosquito testing is a feasible alternative to this has not been widely studied. Applying an individual-based mosquito testing approach, we conducted a 1-month surveillance study of DENV in adult Aedes aegypti mosquitoes in homes of suspected dengue patients during the 2015 peak dengue season in Tarlac City, Philippines to more accurately assess the mosquito infection rate and identify the DENV serotypes and genotypes concurrently co-circulating in mosquitoes and patients there.

METHODS

We performed a one-step multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) assay for the simultaneous detection and serotyping of DENV in patients and individual female Ae. aegypti mosquitoes. Additionally, we performed sequencing and phylogenetic analyses to further characterize the detected DENV serotypes in mosquitoes and patients at the genotype level.

RESULTS

We collected a total of 583 adult Ae. aegypti mosquitoes, of which we individually tested 359 female mosquitoes for the presence of DENV. Ten (2.8%) of the 359 female mosquitoes were positive for the presence of DENV. We detected DENV-1, DENV-2, and DENV-4 in the field-collected mosquitoes, which was consistent with the serotypes concurrently found in infected patients. Sequencing and phylogenetic analyses of the detected DENV serotypes based on the partial sequence of the evelope (E) gene revealed three genotypes concurrently present in the sampled mosquitoes and patients during the study period, namely DENV-1 genotype IV, DENV-2 Cosmopolitan genotype, and DENV-4 genotype II.

CONCLUSIONS

We demonstrated the utility of a one-step multiplex real-time RT-PCR assay for the individual-based DENV surveillance of mosquitoes. Our findings reinforce the importance of detecting and monitoring virus activity in local mosquito populations, which are critical for dengue prevention and control.

Large-scale multivariate forecasting models for Dengue - LSTM versus random forest regression

Effective management of seasonal diseases such as dengue fever depends on timely deployment of control measures prior to the high transmission season. As the epidemic season fluctuates from year to year, the availability of accurate forecasts of incidence can be decisive in attaining control of such diseases. Obtaining such forecasts from classical time series models has proven a difficult task. Here we propose and compare machine learning models incorporating feature selection,such as LASSO and Random Forest regression with LSTM a deep recurrent neural network, to forecast weekly dengue incidence in 790 cities in Brazil. We use multivariate time-series as predictors and also utilize time series from similar cities to capture the spatial component of disease transmission. The LSTM recurrent neural network model attained the highest performance in predicting future incidence on dengue in cities of different sizes.

Predicting dengue outbreaks at neighbourhood level using human mobility in urban areas

Dengue is a vector-borne disease transmitted by the Aedes genus mosquito. It causes financial burdens on public health systems and considerable morbidity and mortality. Tropical regions in the Americas and Asia are the areas most affected by the virus. Fortaleza is a city with approximately 2.6 million inhabitants in northeastern Brazil that, during the recent decades, has been suffering from endemic dengue transmission, interspersed with larger epidemics. The objective of this paper is to study the impact of human mobility in urban areas on the spread of the dengue virus, and to test whether human mobility data can be used to improve predictions of dengue virus transmission at the neighbourhood level. We present two distinct forecasting systems for dengue transmission in Fortaleza: the first using artificial neural network methods and the second developed using a mechanistic model of disease transmission. We then present enhanced versions of the two forecasting systems that incorporate bus transportation data cataloguing movement among 119 neighbourhoods in Fortaleza. Each forecasting system was used to perform retrospective forecasts for historical dengue outbreaks from 2007 to 2015. Results show that both artificial neural networks and mechanistic models can accurately forecast dengue cases, and that the inclusion of human mobility data substantially improves the performance of both forecasting systems. While the mechanistic models perform better in capturing seasons with large-scale outbreaks, the neural networks more accurately forecast outbreak peak timing, peak intensity and annual dengue time series. These results have two practical implications: they support the creation of public policies from the use of the models created here to combat the disease and help to understand the impact of urban mobility on the epidemic in large cities.

Utility of entomological indices for predicting transmission of dengue virus: secondary analysis of data from the Camino Verde trial in Mexico and Nicaragua

Dengue vector entomological indices are widely used to monitor vector density and disease control activities. But the value of these indices as predictors of dengue infection is not established. We used data from the impact assessment of a trial of community mobilization for dengue prevention (Camino Verde) to examine the associations between vector indices and evidence of dengue infection and their value for predicting dengue infection levels. In 150 clusters in Mexico and Nicaragua, two entomological surveys, three months apart, allowed calculation of the mean Container Index, Breteau index, Pupae per Household Index, and Pupae per Container Index across the two surveys. We measured recent dengue virus infection in children, indicated by a doubling of dengue antibodies in paired saliva samples over the three-month period. We examined the associations between each of the vector indices and evidence of dengue infection at household level and at cluster level, accounting for trial intervention status. To examine the predictive value for dengue infection, we constructed receiver operating characteristic (ROC) curves at household and cluster level, considering the four vector indices as continuous variables, and calculated the positive and negative likelihood ratios for different levels of the indices. None of the vector indices was associated with recent dengue infection at household level. The Breteau Index was associated with recent infection at cluster level (Odds ratio 1.36, 95% confidence interval 1.14–1.61). The ROC curve confirmed the weak predictive value for dengue infection of the Breteau Index at cluster level. Other indices showed no predictive value. Conventional vector indices were not useful in predicting dengue infection in Mexico and Nicaragua. The findings are compatible with the idea of sources of infection outside the household which were tackled by community action in the Camino Verde trial.

Vector control is the basis of preventing dengue virus infection. Measurement of dengue vector indices is widely used to monitor dengue control activities, but their utility as predictors of dengue infection is not clear. We used data about vector indices and evidence of recent dengue virus infection from a trial of community mobilization for dengue prevention in Mexico and Nicaragua (Camino Verde), to examine how four standard vector indices could predict dengue infection. Only the Breteau index was associated with evidence of dengue infection, and that only at cluster level. Receiver operating characteristic (ROC) curves confirmed the Breteau Index was only a weak predictor of infection at cluster level; none of the other indices had predictive value. These findings indicate that the four entomological indices studied were not useful predictors of dengue infection. The results are compatible with the idea of sources of infection outside the household which were tackled by community action in the Camino Verde trial.

The TIRS trial: protocol for a cluster randomized controlled trial assessing the efficacy of preventive targeted indoor residual spraying to reduce Aedes-borne viral illnesses in Merida, Mexico

BACKGROUND

Current urban vector control strategies have failed to contain dengue epidemics and to prevent the global expansion of Aedes-borne viruses (ABVs: dengue, chikungunya, Zika). Part of the challenge in sustaining effective ABV control emerges from the paucity of evidence regarding the epidemiological impact of any Aedes control method. A strategy for which there is limited epidemiological evidence is targeted indoor residual spraying (TIRS). TIRS is a modification of classic malaria indoor residual spraying that accounts for Aedes aegypti resting behavior by applying residual insecticides on exposed lower sections of walls (< 1.5 m), under furniture, and on dark surfaces.

METHODS/DESIGN

We are pursuing a two-arm, parallel, unblinded, cluster randomized controlled trial to quantify the overall efficacy of TIRS in reducing the burden of laboratory-confirmed ABV clinical disease (primary endpoint). The trial will be conducted in the city of Merida, Yucatan State, Mexico (population ~ 1million), where we will prospectively follow 4600 children aged 2-15 years at enrollment, distributed in 50 clusters of 5 × 5 city blocks each. Clusters will be randomly allocated (n = 25 per arm) using covariate-constrained randomization. A "fried egg" design will be followed, in which all blocks of the 5 × 5 cluster receive the intervention, but all sampling to evaluate the epidemiological and entomological endpoints will occur in the "yolk," the center 3 × 3 city blocks of each cluster. TIRS will be implemented as a preventive application (~ 1-2 months prior to the beginning of the ABV season). Active monitoring for symptomatic ABV illness will occur through weekly household visits and enhanced surveillance. Annual sero-surveys will be performed after each transmission season and entomological evaluations of Ae. aegypti indoor abundance and ABV infection rates monthly during the period of active surveillance. Epidemiological and entomological evaluation will continue for up to three transmission seasons.

DISCUSSION

The findings from this study will provide robust epidemiological evidence of the efficacy of TIRS in reducing ABV illness and infection. If efficacious, TIRS could drive a paradigm shift in Aedes control by considering Ae. aegypti behavior to guide residual insecticide applications and changing deployment to preemptive control (rather than in response to symptomatic cases), two major enhancements to existing practice.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04343521 . Registered on 13 April 2020. The protocol also complies with the WHO International Clinical Trials Registry Platform (ICTRP) (Additional file 1).

PRIMARY SPONSOR

National Institutes of Health, National Institute of Allergy and Infectious Diseases (NIH/NIAID).

Hidden heterogeneity and its influence on dengue vaccination impact

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

Complex relationships between Aedes vectors, socio-economics and dengue transmission-Lessons learned from a case-control study in northeastern Thailand

BACKGROUND/OBJECTIVES

Dengue fever is an important public health concern in most tropical and subtropical countries, and its prevention and control rest on vector surveillance and control. However, many aspects of dengue epidemiology remain unclear; in particular, the relationship between Aedes vector abundance and dengue transmission risk. This study aims to identify entomological and immunological indices capable of discriminating between dengue case and control (non-case) houses, based on the assessment of candidate indices, as well as individual and household characteristics, as potential risk factors for acquiring dengue infection.

METHODS

This prospective, hospital-based, case-control study was conducted in northeastern Thailand between June 2016 and August 2019. Immature and adult stage Aedes were collected at the houses of case and control patients, recruited from district hospitals, and at patients' neighboring houses. Blood samples were tested by RDT and PCR to detect dengue cases, and were processed with the Nterm-34 kDa salivary peptide to measure the human immune response to Aedes bites. Socioeconomic status, and other individual and household characteristics were analyzed as potential risk factors for dengue.

RESULTS

Study findings showed complex relationships between entomological indices and dengue risk. The presence of DENV-infected Aedes at the patient house was associated with 4.2-fold higher odds of dengue. On the other hand, Aedes presence (irrespective of infectious status) in the patient's house was negatively associated with dengue. In addition, the human immune response to Aedes bites, was higher in control than in case patients and Aedes adult abundance and immature indices were higher in control than in case houses at the household and the neighboring level. Multivariable analysis showed that children aged 10-14 years old and those aged 15-25 years old had respectively 4.5-fold and 2.9-fold higher odds of dengue infection than those older than 25 years.

CONCLUSION

DENV infection in female Aedes at the house level was positively associated with dengue infection, while adult Aedes presence in the household was negatively associated. This study highlights the potential benefit of monitoring dengue viruses in Aedes vectors. Our findings suggest that monitoring the presence of DENV-infected Aedes mosquitoes could be a better indicator of dengue risk than the traditional immature entomological indices.

Associating COVID-19 Severity with Urban Factors: A Case Study of Wuhan

Wuhan encountered a serious attack in the first round of the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in a public health social impact, including public mental health. Based on the Weibo help data, we inferred the spatial distribution pattern of the epidemic situation and its impacts. Seven urban factors, i.e., urban growth, general hospital, commercial facilities, subway station, land-use mixture, aging ratio, and road density, were selected for validation with the ordinary linear model, in which the former six factors presented a globally significant association with epidemic severity. Then, the geographically weighted regression model (GWR) was adopted to identify their unevenly distributed effects in the urban space. Among the six factors, the distribution and density of major hospitals exerted significant effects on epidemic situation. Commercial facilities appear to be the most prevalently distributed significant factor on epidemic situation over the city. Urban growth, in particular the newly developed residential quarters with high-rise buildings around the waterfront area of Hanyang and Wuchang, face greater risk of the distribution. The influence of subway stations concentrates at the adjacency place where the three towns meet and some near-terminal locations. The aging ratio of the community dominantly affects the hinterland of Hankou to a broader extent than other areas in the city. Upon discovering the result, a series of managerial implications that coordinate various urban factors were proposed. This research may contribute toward developing specific planning and design responses for different areas in the city based on a better understanding of the occurrence, transmission, and diffusion of the COVID-19 epidemic in the metropolitan area.

Mayaro Virus Pathogenesis and Transmission Mechanisms

Mayaro virus (MAYV), isolated for the first time in Trinidad and Tobago, has captured the attention of public health authorities worldwide following recent outbreaks in the Americas. It has a propensity to be exported outside its original geographical range, because of the vast distribution of its vectors. Moreover, most of the world population is immunologically naïve with respect to infection with MAYV which makes this virus a true threat. The recent invasion of several countries by Aedesalbopictus underscores the risk of potential urban transmission of MAYV in both tropical and temperate regions. In humans, the clinical manifestations of MAYV disease range from mild fever, rash, and joint pain to arthralgia. In the absence of a licensed vaccine and clinically proven therapeutics against Mayaro fever, prevention focuses mainly on household mosquito control. However, as demonstrated for other arboviruses, mosquito control is rather inefficient for outbreak management and alternative approaches to contain the spread of MAYV are therefore necessary. Despite its strong epidemic potential, little is currently known about MAYV. This review addresses various aspects of MAYV, including its epidemiology, vector biology, mode of transmission, and clinical complications, as well as the latest developments in MAYV diagnosis.

Follow-Up Household Serosurvey in Northeast Brazil for Zika Virus: Sexual Contacts of Index Patients Have the Highest Risk for Seropositivity

BACKGROUND

Zika virus (ZIKV) is a mosquito-borne virus that is also transmitted sexually; however, the epidemiological relevance of ZIKV sexual transmission in endemic regions is unclear.

METHODS

We performed a household-based serosurvey in Northeast Brazil to evaluate the differential exposure to ZIKV and chikungunya virus (CHIKV) among households. Individuals who participated in our previous arboviral disease cohort (indexes) were recontacted and enrolled, and their household members were newly enrolled.

RESULTS

The relative risk of sexual partners being ZIKV-seropositive when living with a ZIKV-seropositive index participant was significantly higher, whereas this was not observed among nonsexual partners of the index. For CHIKV, both sexual and nonsexual partner household members living with a CHIKV-seropositive index had a significantly higher risk of being seropositive. In the nonindex-based dyadic and generalized linear mixed model analyses, the odds of sexual dyads having a concordant ZIKV plaque reduction neutralization test result was significantly higher. We have also analyzed retrospective clinical data according to the participants' exposure to ZIKV and CHIKV.

CONCLUSIONS

Our data suggest that ZIKV sexual transmission may be a key factor for the high ZIKV seroprevalence among households in endemic areas and raises important questions about differential disease from the 2 modes of transmission.

Modeling the relative role of human mobility, land-use and climate factors on dengue outbreak emergence in Sri Lanka

BACKGROUND

More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission.

METHODS

We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1 km × 1 km spatial resolution and a weekly temporal resolution.

RESULTS

Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions.

CONCLUSIONS

Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.

Spatial modes for transmission of chikungunya virus during a large chikungunya outbreak in Italy: a modeling analysis

BACKGROUND

The spatial spread of many mosquito-borne diseases occurs by focal spread at the scale of a few hundred meters and over longer distances due to human mobility. The relative contributions of different spatial scales for transmission of chikungunya virus require definition to improve outbreak vector control recommendations.

METHODS

We analyzed data from a large chikungunya outbreak mediated by the mosquito Aedes albopictus in the Lazio region, Italy, consisting of 414 reported human cases between June and November 2017. Using dates of symptom onset, geographic coordinates of residence, and information from epidemiological questionnaires, we reconstructed transmission chains related to that outbreak.

RESULTS

Focal spread (within 1 km) accounted for 54.9% of all cases, 15.8% were transmitted at a local scale (1-15 km) and the remaining 29.3% were exported from the main areas of chikungunya circulation in Lazio to longer distances such as Rome and other geographical areas. Seventy percent of focal infections (corresponding to 38% of the total 414 cases) were transmitted within a distance of 200 m (the buffer distance adopted by the national guidelines for insecticide spraying). Two main epidemic clusters were identified, with a radius expanding at a rate of 300-600 m per month. The majority of exported cases resulted in either sporadic or no further transmission in the region.

CONCLUSIONS

Evidence suggest that human mobility contributes to seeding a relevant number of secondary cases and new foci of transmission over several kilometers. Reactive vector control based on current guidelines might allow a significant number of secondary clusters in untreated areas, especially if the outbreak is not detected early. Existing policies and guidelines for control during outbreaks should recommend the prioritization of preventive measures in neighboring territories with known mobility flows to the main areas of transmission.

Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation

Understanding geographic population dynamics of mosquitoes is an essential requirement for estimating the risk of mosquito-borne disease transmission and geographically targeted interventions. However, the use of population dynamics measures, such as the intrinsic growth rate, as predictors in spatio-temporal point processes has not been investigated before. In this work we compared the predictive accuracy of four spatio-temporal log-Gaussian Cox models: (i) With no predictors; (ii) mosquito abundance as predictor; (iii) intrinsic growth rate as predictor; (iv) intrinsic growth rate and mosquito abundance as predictors. This analysis is based on Aedes aegypti mosquito surveillance and human dengue data obtained from the urban area of Caratinga, Brazil. We used a statistical Moran Curve approach to estimate the intrinsic growth rate and a zero inflated Poisson kriging model for estimating mosquito abundance at locations of dengue cases. The incidence of dengue cases was positively associated with mosquito intrinsic growth rate and this model outperformed, in terms of predictive accuracy, the abundance and the null models. The latter includes only the spatio-temporal random effect but no predictors. In the light of these results we suggest that the intrinsic growth rate should be investigated further as a potential tool for predicting the risk of dengue transmission and targeting health interventions for vector-borne diseases.

Semi-field evaluation of freestanding transfluthrin passive emanators and the BG sentinel trap as a "push-pull control strategy" against Aedes aegypti mosquitoes

Background

Spatial repellents that drive mosquitoes away from treated areas, and odour-baited traps, that attract and kill mosquitoes, can be combined and work synergistically in a push-pull system. Push-pull systems have been shown to reduce house entry and outdoor biting rates of malaria vectors and so have the potential to control other outdoor biting mosquitoes such as Aedes aegypti that transmit arboviral diseases. In this study, semi-field experiments were conducted to evaluate whether a push-pull system could be used to reduce bites from Aedes mosquitoes.

Methods

The push and pull under investigation consisted of two freestanding transfluthrin passive emanators (FTPE) and a BG sentinel trap (BGS) respectively. The FTPE contained hessian strips treated with 5.25 g of transfluthrin active ingredient. The efficacies of FTPE and BGS alone and in combination were evaluated by human landing catch in a large semi-field system in Tanzania. We also investigated the protection of FTPE over six months. The data were analyzed using generalized linear mixed models with binomial distribution.

Results

Two FTPE had a protective efficacy (PE) of 61.2% (95% confidence interval (CI): 52.2–69.9%) against the human landing of Ae. aegypti. The BGS did not significantly reduce mosquito landings; the PE was 2.1% (95% CI: −2.9–7.2%). The push-pull provided a PE of 64.5% (95% CI: 59.1–69.9%). However, there was no significant difference in the PE between the push-pull and the two FTPE against Ae. aegypti (P = 0.30). The FTPE offered significant protection against Ae. aegypti at month three, with a PE of 46.4% (95% CI: 41.1–51.8%), but not at six months with a PE of 2.2% (95% CI: −9.0–14.0%).

Conclusions

The PE of the FTPE and the full push-pull are similar, indicative that bite prevention is primarily due to the activity of the FTPE. While these results are encouraging for the FTPE, further work is needed for a push-pull system to be recommended for Ae. aegypti control. The three-month protection against Ae. aegypti bites suggests that FTPE would be a useful additional control tool during dengue outbreaks, that does not require regular user compliance.

AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission

Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for [Formula: see text]-borne diseases' environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .

Spatial regression and spillover effects in cluster randomized trials with count outcomes

This paper describes methodology for analyzing data from cluster randomized trials with count outcomes, taking indirect effects as well spatial effects into account. Indirect effects are modeled using a novel application of a measure of depth within the intervention arm. Both direct and indirect effects can be estimated accurately even when the proposed model is misspecified. We use spatial regression models with Gaussian random effects, where the individual outcomes have distributions overdispersed with respect to the Poisson, and the corresponding direct and indirect effects have a marginal interpretation. To avoid spatial confounding, we use orthogonal regression, in which random effects represent spatial dependence using a homoscedastic and dimensionally reduced modification of the intrinsic conditional autoregression model. We illustrate the methodology using spatial data from a pair-matched cluster randomized trial against the dengue mosquito vector Aedes aegypti, done in Trujillo, Venezuela.

Measuring health related quality of life for dengue patients in Iquitos, Peru

Previous studies measuring the health-related quality of life (HRQoL) of individuals with dengue focused on treatment seeking populations. However, the vast majority of global dengue cases are unlikely to be detected by health systems. Representative measurements of HRQoL should therefore include patients with disease not likely to trigger treatment-seeking behavior. This study based in Iquitos, Peru used the Quality of Wellbeing Scale-Self Administered, a survey that enquires about not only physical health, but also psychological health, self-care, mobility, and usual social activities, and rates HRQoL between 0 (death) and 1 (optimum function), to evaluate the impact of dengue on HRQoL. In order to enroll treatment and non treatment-seeking participants, three modalities of participant recruitment were used. In addition to clinic and community-based febrile surveillance, a contact-cluster methodology was also employed to identify infected individuals less likely to seek treatment. We measured changes in HRQoL and identified common areas of health impairment in 73 virologically confirmed dengue cases at 3 time points during the participant's illness; the early-acute (days 0-6 post symptom onset), late-acute (days 7-20), and convalescent illness phases (days 21 +). Participants reported HRQoL related impairments at significantly higher frequency during the early-acute versus convalescent illness phase (Fisher's exact: P<0.01). There was substantial heterogeneity in scores during each illness phase with median scores in the early-acute, late-acute and convalescent phases of 0.56 (IQR: 0.41-0.64), 0.70 (IQR: 0.57-0.94), and 1 (IQR: 0.80-1.00), respectively. In all illness phases participants recruited in clinics had on average the lowest HRQoL scores where as those recruited in the contact clusters had the highest. Only 1 individual who was recruited in the contact-clusters had no reduction in HRQoL score during their illness. These data illustrate that dengue should be considered as a disease that may have significant implications for not only physical health but also psychological health and social functioning. The impact of dengue on the HRQoL of non-treatment-seeking individuals, although lower than the impact among treatment-seeking individuals, is not necessarily trivial.

Predicting re-emergence times of dengue epidemics at low reproductive numbers: DENV1 in Rio de Janeiro, 1986-1990

Predicting arbovirus re-emergence remains challenging in regions with limited off-season transmission and intermittent epidemics. Current mathematical models treat the depletion and replenishment of susceptible (non-immune) hosts as the principal drivers of re-emergence, based on established understanding of highly transmissible childhood diseases with frequent epidemics. We extend an analytical approach to determine the number of ‘skip’ years preceding re-emergence for diseases with continuous seasonal transmission, population growth and under-reporting. Re-emergence times are shown to be highly sensitive to small changes in low R₀ (secondary cases produced from a primary infection in a fully susceptible population). We then fit a stochastic Susceptible–Infected–Recovered (SIR) model to observed case data for the emergence of dengue serotype DENV1 in Rio de Janeiro. This aggregated city-level model substantially over-estimates observed re-emergence times either in terms of skips or outbreak probability under forward simulation. The inability of susceptible depletion and replenishment to explain re-emergence under ‘well-mixed’ conditions at a city-wide scale demonstrates a key limitation of SIR aggregated models, including those applied to other arboviruses. The predictive uncertainty and high skip sensitivity to epidemiological parameters suggest a need to investigate the relevant spatial scales of susceptible depletion and the scaling of microscale transmission dynamics to formulate simpler models that apply at coarse resolutions.

Implementation of geographical information systems for the study of diseases caused by vector-borne arboviruses in Southeast Asia: A review based on the publication record

The spread of mosquito-borne diseases in Southeast Asia has dramatically increased in the latest decades. These infections include dengue, chikungunya and Japanese Encephalitis (JE), high-burden viruses sharing overlapping disease manifestation and vector distribution. The use of Geographical Information Systems (GIS) to monitor the dynamics of disease and vector distribution can assist in disease epidemic prediction and public health interventions, particularly in Southeast Asia where sustained high temperatures drive the epidemic spread of these mosquito-borne viruses. Due to lack of accurate data, the spatial and temporal dynamics of these mosquito-borne viral disease transmission countries are poorly understood, which has limited disease control effort. By following studies carried out on these three viruses across the region in a specific time period revealing general patterns of research activities and characteristics, this review finds the need to improve decision-support by disease mapping and management. The results presented, based on a publication search with respect to diseases due to arboviruses, specifically dengue, chikungunya and Japanese encephalitis, should improve opportunities for future studies on the implementation of GIS in the control of mosquito-borne viral diseases in Southeast Asia.

NS1 Recombinant Proteins Are Efficiently Produced in Pichia pastoris and Have Great Potential for Use in Diagnostic Kits for Dengue Virus Infections

Dengue is one of the major diseases causing global public health concerns. Despite technological advances in vaccine production against all its serotypes, it is estimated that the dengue virus is responsible for approximately 390 million infections per year. Laboratory diagnosis has been the key point for the correct treatment and prevention of this disease. Currently, the limiting factor in the manufacture of dengue diagnostic kits is the large-scale production of the non-structural 1 (NS1) antigen used in the capture of the antibody present in the infected patients' serum. In this work, we demonstrate the production of the non-structural 1 protein of dengue virus (DENV) serotypes 1-4 (NS1-DENV1, NS1-DENV2, NS1-DENV3, and NS1-DENV4) in the methylotrophic yeast Pichia pastoris KM71H. Secreted recombinant protein was purified by affinity chromatography and characterized by SDS-PAGE and ELISA. The objectives of this study were achieved, and the results showed that P. pastoris is a good heterologous host and worked well in the production of NS1DENV 1-4 recombinant proteins. Easy to grow and quick to obtain, this yeast secreted ready-to-use proteins, with a final yield estimated at 2.8-4.6 milligrams per liter of culture. We reached 85-91% sensitivity and 91-93% specificity using IgM as a target, and for anti-dengue IgG, 83-87% sensitivity and 81-93% specificity were achieved. In this work, we conclude that the NS1 recombinant proteins are efficiently produced in P. pastoris and have great potential for use in diagnostic kits for dengue virus infections. The transformed yeast obtained can be used for production in industrial-scale bioreactors.

Evaluation of the usefulness of Aedes aegypti rapid larval surveys to anticipate seasonal dengue transmission between 2012-2015 in Fortaleza, Brazil

Rapid larval surveys have been mandated in nearly every urban Brazilian municipality and promoted by the Pan American Health Organization. These surveys purport to classify arbovirus transmission risk as a basis to triage local surveillance and vector control operations, yet no previous analyses have determined relative risk associated with marginal changes in infestation at administrative and temporal scales relevant to vector control. We estimated associations between entomological indices from six larval surveys and daily incidence rates of confirmed dengue cases in Fortaleza, Brazil using models adjusted for rainfall, and indicators of spatial association. Poor correspondence between infestation and incidence indicates that these surveys may systematically mislead vector control activities and treatment strategies in Fortaleza and in similar cities throughout Latin America. The co-circulation of multiple arboviruses enhances the importance of determining the true informational value of these surveys, and of identifying complementary tools to discern local and inter-annual transmission risk.

Burden of Dengue with Related Entomological and Climatic Characteristics in Surat City, Gujarat, India, 2011-2016: An Analysis of Surveillance Data

We estimated the incidence of laboratory-confirmed dengue patients for Surat city, India, using surveillance data from 2011 to 2016 and described the related entomological indices and climatic factors. There was a rise in incidence from 1.5 to 17.6 per 100,000 population, as the numbers of notified cases have increased because of better surveillance system. The case notification was 1.3 times higher for the public sector than the private sector. The larval indices were below the transmission level (House index, Breteau index < 1%). The median age of dengue patients was 20 years (IQR: 14-28), with a male to female ratio of 1.6:1. Five peripheral vector control units contributed to 1,013 (41.4%) confirmed cases with rising incidence in other units also. The number of dengue patients peaked during post-monsoon. Spearman's correlation of vector density with humidity (r _s = 0.556), rainfall (r _s = 0.644), and number of cases (r _s = 0.708) suggested climate favorable for vector breeding. There is a good system of public-private coordination for dengue surveillance. However, there is a need to reassess the vector indices threshold for transmission in the city.

Effectiveness of an intervention for Aedes aegypti control scaled-up under an inter-sectoral approach in a Colombian city hyper-endemic for dengue virus

Aedes aegypti transmitted arboviral diseases are of significant importance in Colombia, particularly since the 2014/2015 introduction of chikungunya and Zika in the Americas and the increasing spread of dengue. In response, the Colombian government initiated the scaling-up of a community-based intervention under inter and multi-sector partnerships in two out of four sectors in Girardot, one of the most hyper-endemic dengue cities in the country. Using a quasi-experimental research design a scaled-up community-led Aedes control intervention was assessed for its capacity to reduce dengue from January 2010 to August 2017 in Girardot, Colombia. Reported dengue cases, and associated factors were analysed from available data sets from the Colombian disease surveillance systems. We estimated the reduction in dengue cases before and after the intervention using, Propensity Score Matching and an Autoregressive Moving Average model for robustness. In addition, the differences in dengue incidence among scaling-up phases (pre-implementation vs sustainability) and between treatment groups (intervention and control areas) were modelled. Evidence was found in favour of the intervention, although to maximise impact the scaling-up of the intervention should continue until it covers the remaining sectors. It is expected that a greater impact of the intervention can be documented in the next outbreak of dengue in Girardot.

Inapparent dengue in a community living among dengue-positive Aedes mosquitoes and in a hospital in Klang Valley, Malaysia

The public health burden of dengue is most likely under reported. Current dengue control measures only considered symptomatic dengue transmission. Hence, there is a paucity of information on the epidemiology of inapparent dengue. This study reports that many people have been unknowingly exposed to dengue infection. Almost 10% and 70% of individuals without any history of dengue infection and living in a dengue hotspot, in Selangor, Malaysia, were dengue IgM and IgG positive respectively. When dengue-positive mosquitoes were detected in the hotspot, 11 (6.3%) of the 174 individuals tested were found to have dengue viremia, of which 10 were asymptomatic. Besides, upon detection of a dengue-infected mosquito, transmission was already widespread. In a clinical setting, it appears that people living with dengue patients have been exposed to dengue, whether asymptomatic or symptomatic. They can either have circulating viral RNA and/or presence of NS1 antigen. It is also possible that they are dengue seropositive. Collectively, the results indicate that actions taken to control dengue transmission after the first report of dengue cases may be already too late. The current study also revealed challenges in diagnosing clinically inapparent dengue in hyperendemic settings. There is no one best method for diagnosing inapparent dengue. This study demonstrates empirical evidence of inapparent dengue in different settings. Early dengue surveillance in the mosquito population and active serological/virological surveillance in humans can go hand in hand. More studies are required to investigate the epidemiology, seroprevalence, diagnostics, and control of inapparent dengue. It is also crucial to educate the public, health staff and medical professionals on asymptomatic dengue and to propagate awareness, which is important for controlling transmission.

RC, Perkins TA. Optimizing the deployment of ultra-low volume and targeted indoor residual spraying for dengue outbreak response

Recent years have seen rising incidence of dengue and large outbreaks of Zika and chikungunya, which are all caused by viruses transmitted by Aedes aegypti mosquitoes. In most settings, the primary intervention against Aedes-transmitted viruses is vector control, such as indoor, ultra-low volume (ULV) spraying. Targeted indoor residual spraying (TIRS) has the potential to more effectively impact Aedes-borne diseases, but its implementation requires careful planning and evaluation. The optimal time to deploy these interventions and their relative epidemiological effects are, however, not well understood. We used an agent-based model of dengue virus transmission calibrated to data from Iquitos, Peru to assess the epidemiological effects of these interventions under differing strategies for deploying them. Specifically, we compared strategies where spray application was initiated when incidence rose above a threshold based on incidence in recent years to strategies where spraying occurred at the same time(s) each year. In the absence of spraying, the model predicted 361,000 infections [inter-quartile range (IQR): 347,000-383,000] in the period 2000-2010. The ULV strategy with the fewest median infections was spraying twice yearly, in March and October, which led to a median of 172,000 infections [IQR: 158,000-183,000], a 52% reduction from baseline. Compared to spraying once yearly in September, the best threshold-based strategy utilizing ULV had fewer median infections (254,000 vs. 261,000), but required more spraying (351 vs. 274 days). For TIRS, the best strategy was threshold-based, which led to the fewest infections of all strategies tested (9,900; [IQR: 8,720-11,400], a 94% reduction), and required fewer days spraying than the equivalent ULV strategy (280). Although spraying twice each year is likely to avert the most infections, our results indicate that a threshold-based strategy can become an alternative to better balance the translation of spraying effort into impact, particularly if used with a residual insecticide.

The mosquito electrocuting trap as an exposure-free method for measuring human-biting rates by Aedes mosquito vectors

BACKGROUND

Entomological monitoring of Aedes vectors has largely relied on surveillance of larvae, pupae and non-host-seeking adults, which have been poorly correlated with human disease incidence. Exposure to mosquito-borne diseases can be more directly estimated using human landing catches (HLC), although this method is not recommended for Aedes-borne arboviruses. We evaluated a new method previously tested with malaria vectors, the mosquito electrocuting trap (MET) as an exposure-free alternative for measuring landing rates of Aedes mosquitoes on people. Aims were to (i) compare the MET to the BG-sentinel (BGS) trap gold standard approach for sampling host-seeking Aedes vectors; and (ii) characterize the diel activity of Aedes vectors and their association with microclimatic conditions.

METHODS

The study was conducted over 12 days in Quinindé (Ecuador) in May 2017. Mosquito sampling stations were set up in the peridomestic area of four houses. On each day of sampling, each house was allocated either a MET or a BGS trap, which were rotated amongst the four houses daily in a Latin square design. Mosquito abundance and microclimatic conditions were recorded hourly at each sampling station between 7:00-19:00 h to assess variation between vector abundance, trapping methods, and environmental conditions. All Aedes aegypti females were tested for the presence of Zika (ZIKV), dengue (DENV) and chikungunya (CHIKV) viruses.

RESULTS

A higher number of Ae. aegypti females were found in MET than in BGS collections, although no statistically significant differences in mean Ae. aegypti abundance between trapping methods were found. Both trapping methods indicated female Ae. aegypti had bimodal patterns of host-seeking, being highest during early morning and late afternoon hours. Mean Ae. aegypti daily abundance was negatively associated with daily temperature. No infection by ZIKV, DENV or CHIKV was detected in any Aedes mosquitoes caught by either trapping method.

CONCLUSION

We conclude the MET performs at least as well as the BGS standard and offers the additional advantage of direct measurement of per capita human-biting rates. If detection of arboviruses can be confirmed in MET-collected Aedes in future studies, this surveillance method could provide a valuable tool for surveillance and prediction on human arboviral exposure risk.

The Global Expansion of Dengue: How Aedes aegypti Mosquitoes Enabled the First Pandemic Arbovirus

Dengue is an emerging viral disease principally transmitted by the Aedes (Stegomyia) aegypti mosquito. It is one of the fastest-growing global infectious diseases, with 100-400 million new infections a year, and is now entrenched in a growing number of tropical megacities. Behind this rapid rise is the simple adaptation of Ae. aegypti to a new entomological niche carved out by human habitation. This review describes the expansion of dengue and explores how key changes in the ecology of Ae. aegypti allowed it to become a successful invasive species and highly efficient disease vector. We argue that characterizing geographic heterogeneity in mosquito bionomics will be a key research priority that will enable us to better understand future dengue risk and design control strategies to reverse its global spread.

Spatial Dynamics of Chikungunya Virus, Venezuela, 2014

Since chikungunya virus emerged in the Caribbean region in late 2013, ≈45 countries have experienced chikungunya outbreaks. We described and quantified the spatial and temporal events after the introduction and propagation of chikungunya into an immunologically naive population from the urban north-central region of Venezuela during 2014. The epidemic curve (n = 810 cases) unraveled within 5 months with a basic reproductive number of 3.7 and a radial spread traveled distance of 9.4 km at a mean velocity of 82.9 m/day. The highest disease diffusion speed occurred during the first 90 days, and space and space-time modeling suggest the epidemic followed a particular geographic pathway with spatiotemporal aggregation. The directionality and heterogeneity of transmission during the first introduction of chikungunya indicated existence of areas of diffusion and elevated risk for disease and highlight the importance of epidemic preparedness. This information will help in managing future threats of new or reemerging arboviruses.

Zika Virus Infection in Pregnant Women, Yucatan, Mexico

Infection was associated with a high incidence of symptomatic disease but no congenital syndrome.

We report demographic, epidemiologic, and clinical findings for a prospective cohort of pregnant women during the initial phase of Zika virus introduction into Yucatan, Mexico. We monitored 115 pregnant women for signs of active or recent Zika virus infection. The estimated cumulative incidence of Zika virus infection was 0.31 and the ratio of symptomatic to asymptomatic cases was 1.7 (range 1.3–4.0 depending on age group). Exanthema was the most sensitive clinical sign but also the least specific. Conjunctival hyperemia, joint edema, and exanthema were the combination of signs that had the highest specificity but low sensitivity. We did not find evidence of vertical transmission or fetal anomalies, likely because of the low number of pregnant women tested. We also did not find evidence of congenital disease. Our findings emphasize the limited predictive value of clinical features in areas where Zika virus cocirculates with other flaviviruses.

Human Trypanosoma cruzi infection is driven by eco-social interactions in rural communities of the Argentine Chaco

The transmission of Trypanosoma cruzi to humans is determined by multiple ecological, socio-economic and cultural factors acting at different scales. Their effects on human infection with T. cruzi have often been examined separately or using a limited set of ecological and socio-demographic variables. Herein, we integrated the ecological and social dimensions of human infection risk with the spatial distribution patterns of human and vector (Triatoma infestans) infection in rural communities of the Argentine Chaco composed of indigenous people (90% Qom) and a creole minority. We conducted serosurveys in 470 households aiming at complete population enumeration over 2012–2015. The estimated seroprevalence of T. cruzi prior to the implementation of an insecticide spraying campaign (2008) was 29.0% (N = 1,373 in 301 households), and was twice as large in Qom than creoles. Using generalized linear mixed models, human seropositive cases significantly increased with infected triatomine abundance, having a seropositive household co-inhabitant and household social vulnerability (a multidimensional index of poverty), and significantly decreased with increasing host availability in sleeping quarters (an index summarizing the number of domestic hosts for T. infestans). Vulnerable household residents were exposed to a higher risk of infection even at low infected-vector abundances. The risk of being seropositive increased significantly with house infestation among children from stable households, whereas both variables were not significantly associated among children from households exhibiting high mobility within the communities, possibly owing to less consistent exposures. Human infection was clustered by household and at a larger spatial scale, with hotspots of human and vector infection matching areas of higher social vulnerability. These results were integrated in a risk map that shows high-priority areas for targeted interventions oriented to suppress house (re)infestations, detect and treat infected children, and thus reduce the burden of future disease.

Chagas disease is one of the main neglected tropical diseases (NTDs) affecting vulnerable communities in Latin America where transmission by triatomine vectors still occurs. Access to diagnosis and treatment is one of the remaining challenges for sustainable control of Chagas disease in endemic areas. In this study, we integrated the ecological and social determinants of human infection with the spatial component to identify individuals, households and geographic sectors at higher risk of infection. We found that human infection was more prevalent in indigenous people compared to creoles and increased with the abundance of infected vectors and with household social vulnerability (a multidimensional index of poverty). We also found that the social factors modulated the effect of the abundance of infected vectors: vulnerable-household residents were exposed to a higher risk of infection even at low infected-vector abundance, and human mobility within the area determined a lower and more variable exposure to the vector over time. These results were integrated in a risk map that showed high-priority areas, which can be used in designing cost-effective serological screening strategies adapted to resource-constrained areas.

The basic reproductive number for disease systems with multiple coupled heterogeneities

In mathematical epidemiology, a well-known formula describes the impact of heterogeneity on the basic reproductive number, R₀, for situations in which transmission is separable and for which there is one source of variation in susceptibility and one source of variation in infectiousness. This formula is written in terms of the magnitudes of the heterogeneities, as quantified by their coefficients of variation, and the correlation between them. A natural question to ask is whether analogous results apply when there are multiple sources of variation in susceptibility and/or infectiousness. In this paper we demonstrate that with three or more coupled heterogeneities, R₀ under separable transmission depends on details of the distribution of the heterogeneities in a way that is not seen in the well-known simpler situation. We provide explicit formulae for the cases of multivariate normal and multivariate log-normal distributions, showing that R₀ can again be expressed in terms of the magnitudes of the heterogeneities and the pairwise correlations between them. The formulae, however, differ between the two multivariate distributions, demonstrating that no formula of this type applies generally when there are three or more coupled heterogeneities. We see that the results of the formulae are approximately equal when heterogeneities are relatively small and show that an earlier result in the literature (Koella, 1991) should be viewed in this light. We provide numerical illustrations of our results and discuss a setting in which coupled heterogeneities are likely to have a major impact on the value of R₀. We also describe a rather surprising result: in a system with three heterogeneities, R₀ can exhibit non-monotonic behavior with increasing levels of heterogeneity, in marked contrast to the familiar two heterogeneity setting in which R₀ either increases or decreases with increasing heterogeneity.

Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever

Environment and human mobility have been considered as two important factors that drive the outbreak and transmission of dengue fever (DF). Most studies focus on the local environment while neglecting environment of the places, especially epidemic areas that people came from or traveled to. Commuting is a major form of interactions between places. Therefore, this research generates commuting flows from mobile phone tracked data. Geographically weighted Poisson regression (GWPR) and analysis of variance (ANOVA) are used to examine the effect of commuting flows, especially those from/to epidemic areas, on DF in 2014 at the Jiedao level in Guangzhou. The results suggest that (1) commuting flows from/to epidemic areas affect the transmission of DF; (2) such effects vary in space; and (3) the spatial variation of the effects can be explained by the environment of the epidemic areas that commuters commuted from/to. These findings have important policy implications for making effective intervention strategies, especially when resources are limited.

Assessing the interplay between human mobility and mosquito borne diseases in urban environments

Urbanization drives the epidemiology of infectious diseases to many threats and new challenges. In this research, we study the interplay between human mobility and dengue outbreaks in the complex urban environment of the city-state of Singapore. We integrate both stylized and mobile phone data-driven mobility patterns in an agent-based transmission model in which humans and mosquitoes are represented as agents that go through the epidemic states of dengue. We monitor with numerical simulations the system-level response to the epidemic by comparing our results with the observed cases reported during the 2013 and 2014 outbreaks. Our results show that human mobility is a major factor in the spread of vector-borne diseases such as dengue even on the short scale corresponding to intra-city distances. We finally discuss the advantages and the limits of mobile phone data and potential alternatives for assessing valuable mobility patterns for modeling vector-borne diseases outbreaks in cities.

Potential Use of Community-Based Rapid Diagnostic Tests for Febrile Illnesses: Formative Research in Peru and Cambodia

In 2012, the U.S. Defense Threat Reduction Agency Joint Science and Technology Office initiated a program to develop novel point-of-need diagnostic devices for surveillance of emerging infectious diseases including dengue, malaria, plague, and melioidosis. Prior to distribution of devices to observe their correct use among community members in Iquitos, Peru, and Phnom Penh, Cambodia, research was conducted to: 1) assess acceptability of use, including the motivation to use a rapid diagnostic test (RDT) before or instead of seeking care at a health facility, 2) explore comprehension of RDT use instructions, and 3) examine possible strategies for large scale RDT distribution and use at each site. In February 2014, 9 focus group discussions (FGD) with community members and 5 FGD with health professionals were conducted in Iquitos, and 9 FGD with community members and 9 in-depth interviews with health professionals in Phnom Penh. In both places, participants agreed to use the device themselves (involving finger prick) or could identify someone who could do so in their home or neighborhood. The main incentive to RDT use in both sites was the ability for device results to be used for care facilitation (post confirmatory tests), specifically reduced wait times to be seen or obtain a diagnosis. Comprehension of RDT use instructions was assessed in Iquitos by asking some participants to apply the device to research team members; after watching a short video, most steps were done correctly. In Phnom Penh, participants were asked to describe each step after reading the instructions; they struggled with comprehension. Health professionals’ main concerns in both sites were their community’s ability to accurately use the test, handle complicated instructions, and safety (i.e., disposal of lancets). Health system structure and ability to use home diagnostic devices varied in the two disease endemic sites, with substantial challenges in each, suggesting the need for different strategies for RDT large scale community use, and illustrating the value of formative research before deployment of novel technologies.

Development and use of devices to diagnose infectious diseases outside of health facilities (i.e., at home or in remote areas) continues to increase, providing new options for the follow up and treatment options of individuals, depending on the diseases. In this qualitative study, researchers in Iquitos, Peru, and Phnom Penh, Cambodia explored what local people thought about the possible availability of such a device to diagnose dengue and malaria in their own houses, and what would motivate them to use such a device instead of going directly to a health facility for the diagnosis. Participants reported being willing to use device on themselves and were motivated by the possibility that, by using this diagnostic device and taking the result to their health facility, they might be able to obtain quicker and more optimized attention at the health facility; for example, by obtaining a positive result to dengue or malaria on the rapid diagnostic device, they are aware they might still need confirmatory tests, but they would be able to reduce the wait time for obtaining a definitive diagnosis and starting treatment by a full day. Questions regarding accuracy of tests, complicated instructions and safety of using these devices in the community were brought up by participants—individuals living in the communities and local health professionals. Also, in this study, it was clear that if these devices were to be made available in Peru and Cambodia, different strategies for disseminating and using these in the communities would be needed to accommodate for different health infrastructure in both sites.

Local human movement patterns and land use impact exposure to zoonotic malaria in Malaysian Borneo

Human movement into insect vector and wildlife reservoir habitats determines zoonotic disease risks; however, few data are available to quantify the impact of land use on pathogen transmission. Here, we utilise GPS tracking devices and novel applications of ecological methods to develop fine-scale models of human space use relative to land cover to assess exposure to the zoonotic malaria Plasmodium knowlesi in Malaysian Borneo. Combining data with spatially explicit models of mosquito biting rates, we demonstrate the role of individual heterogeneities in local space use in disease exposure. At a community level, our data indicate that areas close to both secondary forest and houses have the highest probability of human P. knowlesi exposure, providing quantitative evidence for the importance of ecotones. Despite higher biting rates in forests, incorporating human movement and space use into exposure estimates illustrates the importance of intensified interactions between pathogens, insect vectors and people around habitat edges.

Hilaire M, St. Ville S, Ryan SJ, Trotman AR, Borbor-Cordova MJ. Co-developing climate services for public health: Stakeholder needs and perceptions for the prevention and control of Aedes-transmitted diseases in the Caribbean

BACKGROUND

Small island developing states (SIDS) in the Caribbean region are challenged with managing the health outcomes of a changing climate. Health and climate sectors have partnered to co-develop climate services to improve the management of emerging arboviral diseases such as dengue fever, for example, through the development of climate-driven early warning systems. The objective of this study was to identify health and climate stakeholder perceptions and needs in the Caribbean, with respect to the development of climate services for arboviruses.

METHODS

Stakeholders included public decision makers and practitioners from the climate and health sectors at the regional (Caribbean) level and from the countries of Dominica and Barbados. From April to June 2017, we conducted interviews (n = 41), surveys (n = 32), and national workshops with stakeholders. Survey responses were tabulated, and audio recordings were transcribed and analyzed using qualitative coding to identify responses by research topic, country/region, and sector.

RESULTS

Health practitioners indicated that their jurisdiction is currently experiencing an increased risk of arboviral diseases associated with climate variability, and most anticipated that this risk will increase in the future. National health sectors reported financial limitations and a lack of technical expertise in geographic information systems (GIS), statistics, and modeling, which constrained their ability to implement climate services for arboviruses. National climate sectors were constrained by a lack of personnel. Stakeholders highlighted the need to strengthen partnerships with the private sector, academia, and civil society. They identified a gap in local research on climate-arbovirus linkages, which constrained the ability of the health sector to make informed decisions. Strategies to strengthen the climate-health partnership included a top-down approach by engaging senior leadership, multi-lateral collaboration agreements, national committees on climate and health, and shared spaces of dialogue. Mechanisms for mainstreaming climate services for health operations to control arboviruses included climatic-health bulletins and an online GIS platform that would allow for regional data sharing and the generation of spatiotemporal epidemic forecasts. Stakeholders identified a 3-month forecast of arboviral illness as the optimal time frame for an epidemic forecast.

CONCLUSIONS

These findings support the creation of interdisciplinary and intersectoral 'communities of practice' and the co-design of climate services for the Caribbean public health sector. By fostering the effective use of climate information within health policy, research and practice, nations will have greater capacity to adapt to a changing climate.

Dengue illness impacts daily human mobility patterns in Iquitos, Peru

Background

Human 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 findings

Through 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/Significance

Our 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.

Dengue is the most important mosquito-borne viral disease of humans worldwide. Due to the limited mobility of the mosquitoes that transmit dengue virus, human mobility can be a key to both understanding an individual’s exposure to the virus and explaining the spread of dengue throughout a population. Accurate disease models should include human mobility; however, changes in human movement patterns due to the presence of symptoms need to be taken into account. We quantified the impact of symptom presence on human mobility throughout the infectious period by analyzing a dataset on the daily movements of dengue virus infected individuals. Accounting for these changing patterns of mobility will improve understanding of the complex relationship between symptom severity, human movement, and dengue virus transmission. Furthermore, dengue transmission models that incorporate symptom-driven mobility changes can be used to evaluate scenarios and strategies for disease prevention.

Risk factors for dengue outbreaks in Odisha, India: A case-control study

BACKGROUND

Environmental and climatic risk factors of dengue outbreak has been studied in detail. However, the socio-epidemiological association with the disease is least explored. The study aims to identify the social and ecological factors associated with emerging dengue in Odisha, India.

METHODS

A population-based case-control study (age and sex matched at the ratio of 1:1) was conducted in six districts of the state in 2017. A structured validated questionnaire was used to collect information for each consenting participant. An ecological household survey was done using a checklist during the month of July-September. Along with the descriptive statistics, conditional logistic regression model was used to calculate the adjusted odds ratio using STATA.

RESULTS

Of 380 cases, nearly 55% were male and the median age was 33years. The adjusted odds of having dengue was nearly three times higher among the people having occupation which demands long travel, presence of breeding sites (1.7; 95% CI 1.2-2.6), presence of swampy area near home (1.5; 95% CI 1.1-2.1) and having travel history close to the index date (1.6; 95% CI 1.1-2.4). People staying in thatched houses had three times higher risk of the disease, however, households keeping the swampy areas clean had 50% less risk for the disease (0.5; 95% CI 0.31-0.67). Nearly 22.2% of cases had a travel history during the index date. Of them, 36% had diagnosis before the travel, whereas, 64% developed the disease after the returning from the travel.

CONCLUSION

Household factors such as occupation and ecological condition of households play important roles in dengue outbreaks in Odisha. However, our study suggests travel/commuting are also essential factors to be considered during disease prevention planning.

Estimating the burden of dengue and the impact of release of wMel Wolbachia-infected mosquitoes in Indonesia: a modelling study

BACKGROUND

Wolbachia-infected mosquitoes reduce dengue virus transmission, and city-wide releases in Yogyakarta city, Indonesia, are showing promising entomological results. Accurate estimates of the burden of dengue, its spatial distribution and the potential impact of Wolbachia are critical in guiding funder and government decisions on its future wider use.

METHODS

Here, we combine multiple modelling methods for burden estimation to predict national case burden disaggregated by severity and map the distribution of burden across the country using three separate data sources. An ensemble of transmission models then predicts the estimated reduction in dengue transmission following a nationwide roll-out of wMel Wolbachia.

RESULTS

We estimate that 7.8 million (95% uncertainty interval [UI] 1.8-17.7 million) symptomatic dengue cases occurred in Indonesia in 2015 and were associated with 332,865 (UI 94,175-754,203) lost disability-adjusted life years (DALYs). The majority of dengue's burden was due to non-severe cases that did not seek treatment or were challenging to diagnose in outpatient settings leading to substantial underreporting. Estimated burden was highly concentrated in a small number of large cities with 90% of dengue cases occurring in 15.3% of land area. Implementing a nationwide Wolbachia population replacement programme was estimated to avert 86.2% (UI 36.2-99.9%) of cases over a long-term average.

CONCLUSIONS

These results suggest interventions targeted to the highest burden cities can have a disproportionate impact on dengue burden. Area-wide interventions, such as Wolbachia, that are deployed based on the area covered could protect people more efficiently than individual-based interventions, such as vaccines, in such dense environments.

Differences in Prevalence of Symptomatic Zika Virus Infection, by Age and Sex-Puerto Rico, 2016

Background

During the outbreak of Zika virus (ZIKV) disease in Puerto Rico in 2016, nonpregnant women aged 20-39 years were disproportionately identified with ZIKV disease. We used household-based cluster investigations to determine whether this disparity was associated with age- or sex-dependent differences in the rate of ZIKV infection or reported symptoms.

Methods

Participation was offered to residents of households within a 100-m radius of the residences of a convenience sample of 19 laboratory-confirmed ZIKV disease cases. Participants answered a questionnaire and provided specimens for diagnostic testing by reverse transcription-polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA).

Results

Among 367 study participants, 114 (31.1%) were laboratory positive for ZIKV infection, of whom 30% reported a recent illness (defined as self-reported rash or arthralgia) attributable to ZIKV infection. Age and sex were not associated with ZIKV infection. Female sex (adjusted prevalence ratio [aPR], 2.28; 95% confidence interval [CI], 1.40, 3.67), age <40 years (aPR, 2.39; 95% CI, 1.55, 3.70), and asthma (aPR, 1.63; 95% CI, 1.12, 2.37) were independently associated with symptomatic infection.

Conclusions

Although neither female sex nor age were associated with an increased prevalence of ZIKV infection, both were associated with symptomatic infection. Further investigation to identify a potential mechanism of age- and sex-dependent differences in reporting symptomatic ZIKV infection is warranted.

Impact of population displacement and forced movements on the transmission and outbreaks of Aedes-borne viral diseases: Dengue as a model

Population displacement and other forced movement patterns following natural disasters, armed conflicts or due to socioeconomic reasons contribute to the global emergence of Aedes-borne viral disease epidemics. In particular, dengue epidemiology is critically affected by situations of displacement and forced movement patterns, particularly within and across borders. In this respect, waves of human movements have been a major driver for the changing epidemiology and outbreaks of the disease on local, regional and global scales. Both emerging dengue autochthonous transmission and outbreaks in countries known to be non-endemic and co-circulation and hyperendemicity with multiple dengue virus serotypes have led to the emergence of severe disease forms such as dengue hemorrhagic fever and dengue shock syndrome. This paper reviews the emergence of dengue outbreaks driven by population displacement and forced movements following natural disasters and conflicts within the context of regional and sub-regional groupings.

Spatial and temporal patterns of dengue incidence in northeastern Thailand 2006-2016

Background

Dengue, a viral disease transmitted by Aedes mosquitoes, is an important public health concern throughout Thailand. Climate variables are potential predictors of dengue transmission. Associations between climate variables and dengue have usually been performed on large-scale first-level national administrative divisions, i.e. provinces. Here we analyze data on a finer spatial resolution in one province, which is often more relevant for effective disease control design. The objective of this study was to investigate the effect of seasonal variations, monthly climate variability, and to identify local clusters of symptomatic disease at the sub-district level based on reported dengue cases.

Methods

Data on dengue cases were retrieved from the national communicable disease surveillance system in Thailand. Between 2006 and 2016, 15,167 cases were recorded in 199 sub-districts of Khon Kaen Province, northeastern Thailand. Descriptive analyses included demographic characteristics and temporal patterns of disease and climate variables. The association between monthly disease incidence and climate variations was analyzed at the sub-district level using Bayesian Poisson spatial regression. A hotspot analysis was used to assess the spatial patterns (clustered/dispersed/random) of dengue incidence.

Results

Dengue was predominant in the 5–14 year-old age group (51.1%). However, over time, dengue incidence in the older age groups (> 15 years) gradually increased and was the most affected group in 2013. Dengue outbreaks coincide with the rainy season. In the spatial regression model, maximum temperature was associated with higher incidence. The hotspot analysis showed clustering of cases around the urbanized area of Khon Kaen city and in rural areas in the southwestern portion of the province.

Conclusions

There was an increase in the number of reported dengue cases in older age groups over the study period. Dengue incidence was highly seasonal and positively associated with maximum ambient temperature. However, climatic variables did not explain all the spatial variation of dengue in the province. Further analyses are needed to clarify the detailed effects of urbanization and other potential environmental risk factors. These results provide useful information for ongoing prediction modeling and developing of dengue early warning systems to guide vector control operations.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4379-3) contains supplementary material, which is available to authorized users.

What Is the Value of Different Zika Vaccination Strategies to Prevent and Mitigate Zika Outbreaks?

BACKGROUND

While the 2015-2016 Zika epidemics prompted accelerated vaccine development, decision makers need to know the potential economic value of vaccination strategies.

METHODS

We developed models of Honduras, Brazil, and Puerto Rico, simulated targeting different populations for Zika vaccination (women of childbearing age, school-aged children, young adults, and everyone) and then introduced various Zika outbreaks. Sensitivity analyses varied vaccine characteristics.

RESULTS

With a 2% attack rate ($5 vaccination), compared to no vaccination, vaccinating women of childbearing age cost $314-$1664 per case averted ($790-$4221/disability-adjusted life-year [DALY] averted) in Honduras, and saved $847-$1644/case averted in Brazil, and $3648-$4177/case averted in Puerto Rico, varying with vaccination coverage and efficacy (societal perspective). Vaccinating school-aged children cost $718-$1849/case averted (≤$5002/DALY averted) in Honduras, saved $819-$1609/case averted in Brazil, and saved $3823-$4360/case averted in Puerto Rico. Vaccinating young adults cost $310-$1666/case averted ($731-$4017/DALY averted) in Honduras, saved $953-$1703/case averted in Brazil, and saved $3857-$4372/case averted in Puerto Rico. Vaccinating everyone averted more cases but cost more, decreasing cost savings per case averted. Vaccination resulted in more cost savings and better outcomes at higher attack rates.

CONCLUSIONS

When considering transmission, while vaccinating everyone naturally averted the most cases, specifically targeting women of childbearing age or young adults was the most cost-effective.

Strategies of host resistance to pathogens in spatially structured populations: An agent-based evaluation

There is growing theoretical evidence that spatial structure can affect the ecological and evolutionary outcomes of host-parasite interactions. Locally restricted interactions have been shown in particular to affect host resistance and tolerance. In this study we investigate the evolution of several types of host disease resistance strategies, alone or in combination, in spatially structured populations. We construct a spatially explicit, individual-based stochastic model where hosts and parasites interact with each other in a spatial lattice, and interactions are restricted to a given neighbourhood of varying size. We investigate several host resistance strategies, including constitutive (expressed in all resistant hosts), induced (expressed only upon infection), and combinations thereof. We show that a costly constitutive resistance cannot reach fixation, whereas an inducible resistance strategy may become fixed in the population if the cost remains low, particularly if it impacts host recovery. We also demonstrate that mixed strategies can be maintained in the host population, and that a higher investment in a recovery-boosting inducible resistance allows for a higher investment in a constitutive response. Our simulations reveal that the spatial structure of the population impacts the selection for resistance in a complex fashion. While single strategies of resistance are generally favoured in less structured populations, mixed strategies can sometimes prevail only in highly structured environments, e.g. when combining constitutive and transmission-blocking induced responses Overall these results shed new light on the dynamics of disease resistance in a spatially-structured host-pathogen system, and advance our theoretical understanding of the evolutionary dynamics of disease resistance, a necessary step to elaborate more efficient and sustainable strategies for disease management.

Recent advances in understanding dengue

This is a selective review of recent publications on dengue clinical features, epidemiology, pathogenesis, and vaccine development placed in a context of observations made over the past half century. Four dengue viruses (DENVs) are transmitted by urban cycle mosquitoes causing diseases whose nature and severity are influenced by interacting factors such as virus, age, immune status of the host, and human genetic variability. A phenomenon that controls the kinetics of DENV infection, antibody-dependent enhancement, best explains the correlation of the vascular permeability syndrome with second heterotypic DENV infections and infection in the presence of passively acquired antibodies. Based on growing evidence in vivo and in vitro, the tissue-damaging DENV non-structural protein 1 (NS1) is responsible for most of the pathophysiological features of severe dengue. This review considers the contribution of hemophagocytic histiocytosis syndrome to cases of severe dengue, the role of movement of humans in dengue epidemiology, and modeling and planning control programs and describes a country-wide survey for dengue infections in Bangladesh and efforts to learn what controls the clinical outcome of dengue infections. Progress and problems with three tetravalent live-attenuated vaccines are reviewed. Several research mysteries remain: why is the risk of severe disease during second heterotypic DENV infection so low, why is the onset of vascular permeability correlated with defervescence, and what are the crucial components of protective immunity?