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Heterogeneity of Dengue Illness in Community-Based Prospective Study, Iquitos, Peru.

ABSTRACT: Measuring heterogeneity of dengue illness is necessary to define suitable endpoints in dengue vaccine and therapeutic trials and will help clarify behavioral responses to illness. To quantify heterogeneity in dengue illness, including milder cases, we developed the Dengue Illness Perceptions Response (IPR) survey, which captured detailed symptom data, including intensity, duration, and character, and change in routine activities caused by illness. During 2016-2019, we collected IPR data daily during the acute phase of illness for 79 persons with a positive reverse transcription PCR result for dengue virus RNA. Most participants had mild ambulatory disease. However, we measured substantial heterogeneity in illness experience, symptom duration, and maximum reported intensity of individual symptoms. Symptom intensity was a more valuable predicter of major activity change during dengue illness than symptom presence or absence alone. These data suggest that the IPR measures clinically useful heterogeneity in dengue illness experience and its relation to altered human behavior.

SUBMITTER: Elson WH

PROVIDER: S-EPMC7454099 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionLong-term disease surveillance data provide a basis for studying drivers of pathogen transmission dynamics. Dengue is a mosquito-borne disease caused by four distinct, but related, viruses (DENV-1-4) that potentially affect over half the world's population. Dengue incidence varies seasonally and on longer time scales, presumably driven by the interaction of climate and host susceptibility. Precise understanding of dengue dynamics is constrained, however, by the relative paucity of laboratory-confirmed longitudinal data.MethodsWe studied 10 years (2000-2010) of laboratory-confirmed, clinic-based surveillance data collected in Iquitos, Peru. We characterized inter and intra-annual patterns of dengue dynamics on a weekly time scale using wavelet analysis. We explored the relationships of case counts to climatic variables with cross-correlation maps on annual and trimester bases.FindingsTransmission was dominated by single serotypes, first DENV-3 (2001-2007) then DENV-4 (2008-2010). After 2003, incidence fluctuated inter-annually with outbreaks usually occurring between October and April. We detected a strong positive autocorrelation in case counts at a lag of ∼ 70 weeks, indicating a shift in the timing of peak incidence year-to-year. All climatic variables showed modest seasonality and correlated weakly with the number of reported dengue cases across a range of time lags. Cases were reduced after citywide insecticide fumigation if conducted early in the transmission season.ConclusionsDengue case counts peaked seasonally despite limited intra-annual variation in climate conditions. Contrary to expectations for this mosquito-borne disease, no climatic variable considered exhibited a strong relationship with transmission. Vector control operations did, however, appear to have a significant impact on transmission some years. Our results indicate that a complicated interplay of factors underlie DENV transmission in contexts such as Iquitos.

Project description: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.

Project description:BackgroundPredictive models can serve as early warning systems and can be used to forecast future risk of various infectious diseases. Conventionally, regression and time series models are used to forecast dengue incidence, using dengue surveillance (e.g., case counts) and weather data. However, these models may be limited in terms of model assumptions and the number of predictors that can be included. Machine learning (ML) methods are designed to work with a large number of predictors and thus offer an appealing alternative. Here, we compared the performance of ML algorithms with that of regression models in predicting dengue cases and outbreaks from 4 to up to 12 weeks in advance. Many countries lack sufficient health surveillance infrastructure, as such we evaluated the contribution of dengue surveillance and weather data on the predictive power of these models.MethodsWe developed ML, regression, and time series models to forecast weekly dengue case counts and outbreaks in Iquitos, Peru; San Juan, Puerto Rico; and Singapore from 1990-2016. Forecasts were generated using available weekly dengue surveillance, and weather data. We evaluated the agreement between model forecasts and actual dengue observations using Mean Absolute Error and Matthew's Correlation Coefficient (MCC).ResultsFor near term predictions of weekly case counts and when using surveillance data, ML models had 21% and 33% less error than regression and time series models respectively. However, using weather data only, ML models did not demonstrate a practical advantage. When forecasting weekly dengue outbreaks 12 weeks in advance, ML models achieved a maximum MCC of 0.61.ConclusionsOur results identified 2 scenarios when ML models are advantageous over regression model: 1) predicting dengue weekly case counts 4 weeks ahead when dengue surveillance data are available and 2) predicting weekly dengue outbreaks 12 weeks ahead when dengue surveillance data are unavailable. Given the advantages of ML models, dengue early warning systems may be improved by the inclusion of these models.

Project description: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.

Project description:BackgroundKnowledge of spatial patterns of dengue virus (DENV) infection is important for understanding transmission dynamics and guiding effective disease prevention strategies. Because movement of infected humans and mosquito vectors plays a role in the spread and persistence of virus, spatial dimensions of transmission can range from small household foci to large community clusters. Current understanding is limited because past analyses emphasized clinically apparent illness and did not account for the potentially large proportion of inapparent infections. In this study we analyzed both clinically apparent and overall infections to determine the extent of clustering among human DENV infections.Methodology/principal findingsWe conducted spatial analyses at global and local scales, using acute case and seroconversion data from a prospective longitudinal cohort in Iquitos, Peru, from 1999-2003. Our study began during a period of interepidemic DENV-1 and DENV-2 transmission and transitioned to epidemic DENV-3 transmission. Infection status was determined by seroconversion based on plaque neutralization testing of sequential blood samples taken at approximately six-month intervals, with date of infection assigned as the middate between paired samples. Each year was divided into three distinct seasonal periods of DENV transmission. Spatial heterogeneity was detected in baseline seroprevalence for DENV-1 and DENV-2. Cumulative DENV-3 seroprevalence calculated by trimester from 2001-2003 was spatially similar to preexisting DENV-1 and DENV-2 seroprevalence. Global clustering (case-control Ripley's K statistic) appeared at radii of ?200-800 m. Local analyses (Kuldorf spatial scan statistic) identified eight DENV-1 and 15 DENV-3 clusters from 1999-2003. The number of seroconversions per cluster ranged from 3-34 with radii from zero (a single household) to 750 m; 65% of clusters had radii >100 m. No clustering was detected among clinically apparent infections.Conclusions/significanceSeroprevalence of previously circulating DENV serotypes can be a predictor of transmission risk for a different invading serotype and, thus, identify targets for strategically placed surveillance and intervention. Seroprevalence of a specific serotype is also important, but does not preclude other contributing factors, such as mosquito density, in determining where transmission of that virus will occur. Regardless of the epidemiological context or virus serotype, human movement appears to be an important factor in defining the spatial dimensions of DENV transmission and, thus, should be considered in the design and evaluation of surveillance and intervention strategies.

Project description:Dengue is one of the most important vector-borne diseases, resulting in an estimated hundreds of millions of infections annually throughout the tropics. Control of dengue is heavily dependent upon control of its primary mosquito vector, Aedes aegypti. Innovative interventions that are effective at targeting the adult stage of the mosquito are needed to increase the options for effective control. The use of insecticide-treated curtains (ITCs) has previously been shown to significantly reduce the abundance of Ae. aegypti in and around homes, but the impact of ITCs on dengue virus (DENV) transmission has not been rigorously quantified. A parallel arm cluster-randomized controlled trial was conducted in Iquitos, Peru to quantify the impact of ITCs on DENV seroconversion as measured through plaque-reduction neutralization tests. Seroconversion data showed that individuals living in the clusters that received ITCs were at greater risk to seroconverting to DENV, with an average seroconversion rate of 50.6 per 100 person-years (PY) (CI: 29.9-71.9), while those in the control arm had an average seroconversion rate of 37.4 per 100 PY (CI: 15.2-51.7). ITCs lost their insecticidal efficacy within 6 months of deployment, necessitating re-treatment with insecticide. Entomological indicators did not show statistically significant differences between ITC and non-ITC clusters. It's unclear how the lack of protective efficacy reported here is attributable to simple failure of the intervention to protect against Ae. aegypti bites, or the presence of a faulty intervention during much of the follow-up period. The higher risk of dengue seroconversion that was detected in the ITC clusters may have arisen due to a false sense of security that inadvertently led to less routine protective behaviors on the part of households that received the ITCs. Our study provides important lessons learned for conducting cluster randomized trials for vector control interventions against Aedes-transmitted virus infections.

Project description:BackgroundChildhood obesity is an urgent worldwide concern associated with increased morbidity in adulthood. Healthcare professionals (HCPs) are well placed to influence childhood obesity trends and implement interventions. English-language studies regarding HCPs' perceptions of childhood obesity are limited to high-income countries. Peru is an upper-middle-income country with regional disparities in childhood obesity prevalence. This qualitative study aims to explore HCPs' perceptions of childhood obesity in Iquitos, Peru, where prevalence is relatively low.MethodsTwenty-one HCPs with child healthcare experience were purposively recruited from two primary healthcare centres. Semi-structured, individual interviews were conducted with a translator and audio recorded. Transcribed data were analysed using thematic analysis.ResultsEight themes were identified and divided into four categories: (1) HCPs' perceptions and attitudes towards childhood obesity (level of concern regarding childhood obesity, perceived consequences of childhood obesity); (2) Factors which HCPs perceive to be important in the development of childhood obesity (parental factors, contextual factors); (3) HCPs' perceptions of their role in childhood obesity prevention and management (educating parents about childhood obesity, regular monitoring of child growth); and (4) Barriers and facilitators in childhood obesity prevention and management (in healthcare, in schools).ConclusionsHCPs had a low level of concern regarding childhood obesity in Iquitos and prioritised undernutrition. Parental factors were perceived to be the most influential in the development of childhood obesity. HCPs perceived themselves to have minimal influence due to prevailing positive views of excess weight and difficulties engaging parents. Educating parents about childhood obesity was felt to be essential to prevention and management although regular monitoring of child growth and home healthcare visits were viewed as useful additional measures. This study can help to inform the development of targeted public health strategies which are sensitive to local contexts and could prevent the upward childhood obesity trends evident elsewhere in Peru.

Project description:BackgroundTransmission of dengue virus (DENV) from humans to mosquitoes represents a critical component of dengue epidemiology. Examinations of this process have generally been hampered by a lack of methods that adequately represent natural acquisition of DENV by mosquitoes from humans. In this study, we assessed artificial and natural blood feeding methods based on rates of DENV infection and dissemination within mosquitoes for use in a field-based epidemiological cohort study in Iquitos, Peru.Methodology/principal findingsOur study was implemented, stepwise, between 2011 and 2015. Participants who were 5 years and older with 5 or fewer days of fever were enrolled from ongoing clinic- and neighborhood-based studies on dengue in Iquitos. Wild type, laboratory-reared Aedes aegypti were fed directly on febrile individuals or on blood collected from participants that was either untreated or treated with EDTA. Mosquitoes were tested after approximately 14 days of extrinsic incubation for DENV infection and dissemination. A total of 58 participants, with viremias ranging from 1.3 × 10(2) to 2.9 × 10(6) focus-forming units per mL of serum, participated in one or more feeding methods. DENV infection and dissemination rates were not significantly different following direct and indirect-EDTA feeding; however, they were significantly lower for mosquitoes that fed indirectly on blood with no additive. Relative to direct feeding, infection rates showed greater variation following indirect-EDTA than indirect-no additive feeding. Dissemination rates were similar across all feeding methods. No differences were detected in DENV infection or dissemination rates in mosquitoes fed directly on participants with different dengue illness severity.Conclusions/significanceOur study demonstrates the feasibility of using direct and indirect feeding methods for field-based studies on vector competence. Direct mosquito feeding is preferable in terms of logistical ease, biosecurity, and reliability.

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Heterogeneity of Dengue Illness in Community-Based Prospective Study, Iquitos, Peru.

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