Seroprevalence, incidence estimates, and environmental risk factors for dengue, chikungunya, and Zika infection amongst children living in informal urban settlements in Indonesia and Fiji

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Rosser, John J. Openshaw, Audrie Lin, Ruzka R. Taruc, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5141509/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jan, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted 4 You are reading this latest preprint version Abstract Background The burden of Aedes aegypti -transmitted viruses such as dengue, chikungunya, and Zika are increasing globally, fueled by urbanization and climate change, with some of the highest current rates of transmission in Asia. Local factors in the built environment have the potential to exacerbate or mitigate transmission. Methods In 24 informal urban settlements in Makassar, Indonesia and Suva, Fiji, we tested children under 5 years old for evidence of prior infection with dengue, chikungunya, and Zika viruses by IgG serology. We used a catalytic model using seroprevalence and mean age to estimate annual incidence of dengue in each country. We also conducted detailed questionnaires to evaluate environmental risk factors for a positive serology result. Dengue risk factors were evaluated for individual children by univariate and multivariable logistic regression accounting for settlement as a fixed effect. Trash and flooding were additionally evaluated as dengue risk factors at the settlement level by univariate linear regression. Results In Fiji and Indonesia respectively, 46% and 33% of children under 5 years old were seropositive for dengue, 3% and 3% for chikungunya, and 9% and 2% for Zika. In Indonesia, children living in a household where trash is routinely collected and removed were significantly less likely to be dengue seropositive in both unadjusted and adjusted models [adjusted model: OR 0.3 (95% CI: 0.1–0.8)]. In Indonesia, settlements with a higher proportion of households reporting flooding also had lower dengue rates (slope = 0.44; p-value: <0.05). Conclusions Household trash collection and community flood management are important targets for interventions to mitigate the increasing risk of Aedes aegypti -transmitted viruses. Aedes trash waste arboviruses vector borne diseases dengue built environment Figures Figure 1 Background Warming temperatures and extreme weather events are expanding the range and availability of suitable habitats for Aedes aegypti , the primary mosquito vector for dengue, chikungunya, and Zika viruses[ 1 – 6 ]. Dengue virus is the most common arbovirus globally, has increased exponentially over the last several decades[ 7 ], and causes an acute febrile illness with clinical presentations ranging from asymptomatic to life-threatening hemorrhage and shock[ 8 ]. While less prevalent than dengue, chikungunya and Zika viruses have also emerged as global problems over recent decades and can cause long term morbidity[ 8 – 12 ]. As the climate continues to change, generating reliable estimates of infection rates for Ae. aegypti transmitted viral infections is essential to monitoring changing transmission dynamics and generating models to forecast future risk. Current estimates of recent disease transmission are limited by a reliance on acute febrile surveillance and cross-sectional serology studies in the general population. Acute febrile surveillance underreports the true burden of disease, only tracking cases that come to the hospital and receive a correct diagnosis. Dengue, chikungunya, and Zika infections all have non-specific clinical presentations; and diagnostic tests for infections are not readily available in many medical systems and have a limited window for detection. Furthermore, surveillance reporting requirements and resources can vary between locations and over time. An alternative to acute febrile surveillance is estimating disease burden with cross-sectional serology studies. Seroprevalence studies are also limited in that a positive serology indicates any past infection, not just recent infection, and antibody levels wane over time. However, in places with a high incidence of disease, serology studies performed in young children can overcome these limitations and provide insights into recent disease incidence. While climate change may be fueling the spread of Ae. aegypti- transmitted viruses, local environmental factors can also affect an individual’s risk of exposure. Ae. aegypti mosquitoes breed in small containers of fresh water, including water storage containers, trash, discarded tires, and gutters on houses that fill with rainwater[ 13 – 25 ]. Local conditions, including temperature, humidity, and air circulation, also affect where the adult mosquitoes reside[ 5 , 26 , 27 ]. The role of the built environment, such as housing construction[ 24 , 27 – 29 ] and landscaping[ 27 ], in modulating dengue risk is beginning to be recognized. As climate change exacerbates Ae. aegypti -transmitted viruses, there is a critical need for better understanding modifiable features of the built environment that attenuate transmission risk and can be targets for local interventions. Informal urban settlements in Indonesia and Fiji have known high rates of dengue infection[ 1 , 30 – 32 ]. The hot, humid climate is highly suitable for the Ae. aegypti lifecycle and virus incubation[ 33 – 35 ]. Fluctuations between drought and flooding in the region[ 36 , 37 ] and inadequate water infrastructure[ 38 ] in the settlements results in pooling of rainwater during heavy rains and storage of water during dry periods, both providing breeding grounds for Ae. aegypti mosquitoes. Inadequate trash management can additionally provide containers for mosquito oviposition[ 13 , 27 ]. The objectives of this study are to measure seroprevalence and estimate the incidence of dengue, chikungunya, and Zika infections in young children living in informal urban settlements in Indonesia and Fiji. This study also aims to evaluate local environmental risk factors for Ae. aegypti – transmitted arbovirus infections. Methods Study Population The Revitalizing Informal Settlements and their Environment (RISE) study was conducted in 24 informal urban settlements in Makassar, Indonesia and Suva, Fiji with enrollment and study procedures previously described[ 39 ]. This study involved questionnaires and biological sampling of children between the ages of 6 months to 5 years old living in the RISE sites in 2018 and 2019 who were enrolled in the study and whose parents consented for their participation. Questionnaires Baseline questionnaires were used to assess household and individual demographic information and environmental exposures that were hypothesized to be predictive of dengue, chikungunya, and Zika seropositivity. Serology testing We performed dengue, chikungunya, and Zika virus serology testing on serum samples collected from children under 5 years old enrolled in the RISE study who underwent sampling in 2018 in Indonesia and in 2019 in both Indonesia and Fiji. Serum samples were stored in Sarstedt screw cap tubes at -80°C for four years prior to serology testing. Serology testing was performed in duplicate using Abcam IgG ELISA’s kits to evaluate for evidence of prior exposure to dengue, chikungunya, and Zika viruses. Duplicate positive, negative, and cut-off controls were used on each plate. Following Abcam kit protocols, antibody titers were converted into standard units based on average cut-off values and all samples with titers greater than 10 standard units were considered positive. Seropositivity rates are reported for each arbovirus and for the proportion of children with evidence of multiple prior infections. Incidence estimates Catalytic models estimate the force of primary infection, or incidence rate, using seroprevalence data in diseases where seroprevalence is a marker of any past infection and indicates lifelong immunity[ 40 , 41 ]. Dengue infection, particularly in young children, meets these criteria and catalytic models have previously been used to estimate dengue incidence[ 42 ]. Using a catalytic model, we estimated dengue incidence in each country assuming a constant force of infection over time whereby incidence = 1–(1–seroprevalence)^(1/ mean years of exposure) . Risk factor analysis Baseline demographic and environmental risk factors for dengue infection in the children enrolled in the RISE study were evaluated by a univariate logistic regression model and a multivariable logistic regression accounting for settlement as a fixed effect and individual characteristics thought to be plausible risk factors for dengue as random effects. For the two breastfeeding questions, “breastfeeding currently” was retained in the multivariable model since it was significant in the univariate model in Fiji; however, a sensitivity analysis was also performed which replaced “breastfed in the past 3 months” in the model, which did not change the findings. As a further exploration of the potential impact of household variables that might have an impact on the surrounding settlement arbovirus exposure risk – namely flooding and trash collection - we also conducted univariate linear regression at the settlement level to evaluate whether the proportion of households reporting flooding and trash collection were predictive of dengue seropositivity across the settlement. This settlement analysis was restricted to settlements with at least 10 children tested and multivariable regression was not conducted given the small sample size. All risk factor analyses were conducted to evaluate risk of dengue infection. Given the overall low chikungunya and Zika seroprevalence and the fact that the majority of individuals with evidence of either of these two infections were seropositive for dengue, risk factor assessment was not conducted for these other viruses. All analyses were performed in R version 2023.06.1. Ethics : Ethics review and approval was provided by participating universities and local IRBs, including: Monash University Human Research Ethics Committee (Melbourne, Australia; project ID 35903), Ministry of Research, Technology and Higher Education Ethics Committee of Medical Research at the Faculty of Medicine, Universitas Hasanuddin (Makassar, Indonesia; protocol UH18020110), and Fiji National University College Human Health Research Ethics Committee (CHREC ID 137.19). This trial is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12618000633280; https://www.anzctr.org.au/ ). Results Demographic Characteristics A total of 191 children in Fiji and 181 children in Indonesia were included in the study. Overall, the mean age of children at the time of serum sample collection was 3.3 years old and male children comprised 61% of the study population. Breastfeeding, household trash collection, having a household member who grows plants, and porous building materials for household construction was more commonly reported amongst participants in Fiji than Indonesia. In contrast, flooding in or around the house was more commonly reported in Indonesia. (Table 1 ) Table 1 Baseline characteristics of children in Fiji and Indonesia Fiji n (%) (N = 191) Indonesia n (%) (N = 181) Child characteristics Male 107/191 (56%) 119/181 (66%) Age: mean (sd) 3.2 (1.2) 3.5 (1.0) Breastfed in the past 3 months 50/185 (27%) 20/181 (11%) Breastfeeding currently 35/185 (19%) 17/181 (9%) Ethnicity & religion of household respondent Ethnicity I-Taukei 168/189 (89%) Indo Fijian 11/189 (6%) Other Fijian or Mixed 10/189 (5%) Makassar 108/163 (66%) Bugis 11/163 (7%) Toraja 8/163 (5%) Other Indonesian or Mixed 36/163 (22%) Religion Christian 76/189 (40%) Lotu Vakarisito 101/189 (53%) Other or Mixed (Fiji) 12/189 (6%) Islam 152/163 (93%) Other or Mixed (Indonesia) 11/163 (7%) Household characteristics Reports many mosquito bites 1 156/191 (82%) 151/160 (94%) Household trash collection 2 161/191 (84%) 103/160 (64%) Grows plants 3 126/191 (66%) 79/160 (49%) Experiences flooding in or outside the house 52/191 (27%) 86/181 (48%) Flooring made of porous material 4 182/191 (95%) 53/160 (33%) Walls made of porous material 4 84/191 (44%) 37/160 (23%) Stores water 145/191 (76%) 146/160 (91%) Abbreviations: sd = standard deviation In Fiji, there were 2 children with missing data on ethnicity and religion and 6 children with missing data on breastfeeding status. In Indonesia, there were 21 children with missing data on various household characteristics. 1 Household respondent reported that in the past 6 weeks they experienced mosquitoes biting inside the house at least several times a week. 2 Trash is always collected and taken away or taken to a neighborhood collection point. 3 A household member grows plants in the house, garden, or settlement croplands. 4 Porous housing material included wood, bamboo, woven mat, dirt, and tent material; in contrast, non-porous materials included cement, ceramic tiles, bricks, laminate, granite, and metal. Seropositivity Dengue IgG seropositivity was high in both countries, with 46% of children in Fiji and 33% of children in Indonesia demonstrating evidence of prior dengue exposure. Zika seropositivity was higher in Fiji than Indonesia. Chikungunya seropositivity was low but detectable in both countries. A total of 19 children (10%) in Fiji and 7 children (3%) in Indonesia were seropositive for more than one arbovirus. (Table 2 ) Table 2 IgG Seropositivity of Aedes-transmitted arboviruses in children under 5 years old Arbovirus Fiji (N = 191) Indonesia (N = 181) All results Dengue 88 (46.1%) 59 (32.6%) Chikungunya 5 (2.6%) 5 (2.8%) Zika 18 (9.4%) 3 (1.7%) Multiple infections Dengue & Chikungunya 4 (2.1%) 5 (2.8%) Dengue & Zika 14 (7.3%) 2 (1.1%) Dengue & Chikungunya & Zika 1 (0.5%) 0 (0%) Abbreviations: IgG = Immunoglobulin G. "All results" includes all children who tested positive on IgG ELISA for each arbovirus, regardless of results of the other serology tests. "Multiple infections" refers to the number of children who tested positive on multiple serology tests, indicating infection with multiple arboviruses during their lifetime, although not necessarily co-infection at the same time. Dengue seropositivity overall increased with age, with the exception of the 0.5 to < 1 year olds which showed a relatively high seropositivity but had very low numbers of participants. By the age of 4 to 5 years old, 71% and 51% of the children in Fiji and Indonesia respectively had been infected with dengue (Table 3 ). Using a catalytic model, we estimated an annual incidence rate of 18% in Fiji and 11% in Indonesia. Although seroprevalence rates of chikungunya and Zika were too low to model incidence, seropositivity was found in multiple age groups. Table 3 Dengue seropositivity by age Age (years) Fiji N = 191 Indonesia N = 181 0.5 to < 1* 1/10 (10%) 1/3 (33%) 1 to < 2 2/28 (7%) 1/17 (6%) 2 to < 3 10/37 (27%) 9/36 (25%) 3 to < 4 33/57 (58%) 14/58 (24%) 4 to < 5 42/59 (71%) 34/67 (51%) Dengue risk increases with age in both countries, consistent with continuous increasing exposure over time. This is consistent with endemic transmission rather than a single epidemic. *Seroprevalence estimates may be artificially elevated for this age category because this only includes children > 6 months, not across the entire range. Estimates in this group are also less precise due to small sample size in this group. Demographic and environmental risk factors for dengue : Age was a significant predictor of dengue serostatus amongst children in Fiji and Indonesia in both unadjusted and adjusted models [Adjusted models - Fiji: OR 4.0 (95% CI: 2.5–6.3); Indonesia: OR 2.2 (95% CI: 1.4–3.6)]. In Indonesia, children living in a household with trash collection were significantly less likely to be dengue seropositive in both unadjusted and adjusted models [Adjusted model OR 0.3 (95% CI: 0.1–0.8)]. Living in a house made of porous flooring material was also protective against dengue exposure amongst children in Indonesia, although this was only significant in the unadjusted model [OR 0.4 (95% CI: 0.2–0.9)]. In Fiji, children who were currently breastfeeding at the time of serum sampling were less likely to be seropositive for dengue in the unadjusted model [OR 0.3 (95% CI: 0.1–0.7)], but this did not remain statistically significant in the adjusted model accounting for age. (Table 4 ) Household flooding was not a significant predictor of individual dengue seropositivity in Indonesia or Fiji; however, in Indonesia, settlements with a higher proportion of households reporting flooding had lower rates of dengue. (Figure) Table 4 Demographic and environmental risk factors for dengue exposure amongst children in Fiji and Indonesia Fiji Indonesia Risk Factors Negative (N = 103) Positive (N = 88) Unadjusted Model OR (95% CI) Adjusted Model OR (95% CI) Negative (N = 122) Positive (N = 59) Unadjusted Model OR (95% CI) Adjusted Model OR (95% CI) Male gender 57 (55%) 50 (57%) 1.1 (0.6–1.9) 0.9 (0.4–1.9) 83 (68%) 36 (61%) 0.7 (0.4–1.4) 0.9 (0.4–2.1) Age (years) 2.6 (1.2) 3.8 (0.8) 2.9 (2.1–4.1) * 4.0 (2.5–6.3)* 3.3 (1.0) 3.9 (0.9) 2.0 (1.4–2.9) * 2.2 (1.4–3.6)* Breastfed in the past 3 months 33/102 (32%) 17/83 (21%) 0.5 (0.3–1.0) 2.7 (1–7.8) 17 (14%) 3 (5%) 0.3 (0.1–1) 0.7 (0.1–3.9) Breastfeeding currently 27/102 (26%) 8/83 (10%) 0.3 (0.1–0.7) * 1.5 (0.5–4.8) 14 (11%) 3 (5%) 0.4 (0.1–1.3) 0.9 (0.2–4.9) Reports many mosquito bites 1 82 (80%) 74 (84%) 1.4 (0.6–2.9) 0.6 (0.2–1.7) 104/111 (94%) 47/49 (96%) 1.6 (0.4–10.9) 3.3 (0.5–21.5) Household trash collection 2 86 (83%) 75 (85%) 1.1 (0.5–2.5) 2.2 (0.7–7) 79/111 (71%) 24/49 (49%) 0.4 (0.2–0.8) * 0.3 (0.1–0.8)* Grows plants 3 65 (63%) 61 (69%) 1.3 (0.7–2.4) 1.3 (0.6–3.2) 54/111 (49%) 25/49 (51%) 1.1 (0.6–2.2) 1.1 (0.5–2.4) Experiences flooding in or outside the house 27 (26%) 25 (28%) 1.1 (0.6–2.1) 0.5 (0.2–1.4) 59 (48%) 27 (46%) 0.9 (0.5–1.7) 1.6 (0.7–3.7) Flooring made of porous material 4 97 (94%) 85 (97%) 1.8 (0.4–8.5) 2.5 (0.4–15.3) 43/111 (39%) 10/49 (20%) 0.4 (0.2–0.9) * 0.4 (0.2–1.2) Walls made of porous material 4 47 (46%) 37 (42%) 0.9 (0.5–1.5) 0.8 (0.3–1.7) 28/111 (25%) 9/49 (18%) 0.7 (0.3–1.5) 1.0 (0.4–2.7) Stores water 78 (76%) 67 (76%) 1.0 (0.5–2.0) 0.9 (0.4–2.3) 101/111 (92%) 45/49 (90%) 0.8 (0.3–2.7) 0.5 (0.1–2.3) Abbreviations: OR = odds ratio; CI = confidence interval * Indicates statistically significant result with a threshold of p < 0.05 Denominators provided for all variables with missing data. In the adjusted models, we ran a second model for breastfeeding currently that excluded breastfed in the past 3 months and a second model for flooring and walls made of porous material that excluded the individual variables for flooring and walls. 1 Household respondent reported that in the past 6 weeks they experienced mosquitoes biting inside the house at least several times a week. 2 Trash is always collected and taken away or taken to a neighborhood collection point 3 A household member grows plants in the house, garden, or settlement croplands. 4 Porous housing material included wood, bamboo, woven mat, dirt, and tent material; in contrast, non-porous materials included cement, ceramic tiles, bricks, laminate, granite, and metal. Figure. Settlement level dengue seropositivity versus flooding and trash collection rates *Indicates statistically significant result with p-value < 0.05. Settlements in Indonesia with a higher percentage of houses that reported flooding in or around their house had significantly lower dengue seropositivity rates, suggestive that flooding could reduce breeding habitats. Settlements in both Fiji and Indonesia with a higher percentage of houses reporting trash collection seem to have lower dengue seropositivity rates, consistent with the individual level analysis, but this was not found to be significant at the settlement level. In Fiji, trash collection was found to be high across most settlements, making any potential correlation to dengue risk difficult to ascertain. Discussion Our study found a high prevalence of dengue in Fiji and Indonesia, with over half of children in each country having had an infection by the age of five years old. Although chikungunya and Zika exposure was lower, a seroprevalence of 2–9% in such young children suggests ongoing transmission of these other Ae. aegypti – transmitted viruses in these countries as well. Our dengue seroprevalence estimates are similar to those found in a 2014 study of urban children across Indonesia[ 32 ], and in South Sulawesi in particular[ 43 ], corroborating the high rates of dengue in Indonesia. Although dengue circulation in Fiji is well established with many known outbreaks over the years, dengue seroprevalence and incidence data across Fiji is limited[ 44 , 45 ]. Our study is one of the few studies providing such estimates and showed high circulation of dengue in Suva, the capital city located in the Central District of the Island of Vitu Levi. Our study also showed a steady increase in seropositivity for each year of age in children under 5 years old in both countries, indicating high levels of non-epidemic transmission. Other studies in Indonesia and Fiji looking at demographic or environmental risk factors have not identified significant risk factors for dengue seropositive test results[ 32 , 44 ]. Our study focused on environmental features of the built environment that would be expected to increase dengue exposure and looked at the youngest children as they acquire their first dengue infections, thus giving a potentially unique window into risk factors in places with very high levels of risk. Trash being collected and removed from the household in our cohort in Indonesia was a significant protective factor against dengue infection in the individual level analysis. In the secondary analysis at the settlement level, we observe a similar correlation between settlement trash collection and settlement dengue risk. Although the settlement level analysis was not found to be statistically significantly, we suspect this is due to inadequate statistical power with this small sample size or that household practices are a stronger driver of risk given the relatively short flight range of Ae. aegypti. We did not find a significant association between trash collection and dengue in the Fiji cohort in either the individual or community level analyses. In Fiji, the higher overall dengue risk may overwhelm such individual environmental risk; furthermore, trash collection was very common (83%) in Fiji, diminishing our power to detect a difference in dengue exposure in this cohort. Ae. aegypti breed in small containers of water[ 13 , 14 , 18 , 20 ] and have a relatively short range of about 100 meters[ 46 ]. Our findings in Indonesia corroborate other studies demonstrating Ae. aegypti breeding in trash filled with rainwater [ 13 , 27 , 47 – 49 ] and implicate household trash disposal practices as a dengue exposure risk. Our study adds to the existing literature not only by showing this direct association between household trash disposal practices and individual disease risk but also by highlighting the risk posed by inadequate trash collection in informal settlements. Because they are not legally recognized neighborhoods, informal settlements are often excluded from government trash collection programs, particularly in Makassar, Indonesia. Our study indicates that household trash removal could decrease disease exposure and endorses the inclusion of informal settlements in regular government trash collection programs. The impact of flooding on dengue risk is complex and remains poorly understood. While dengue outbreaks following large floods frequently make news headlines[ 50 – 52 ], it is unclear whether these outbreaks are due to the floods themselves, heavy rainfall regardless of flooding, or an extended duration of pooled water as floodwaters recede. Other studies have proposed that while heavy rainfall fills up potential Ae. aegypti breeding grounds with water, severe flooding may in fact flush out those small containers holding water and Ae. aegypti larva, or wash away trash containers from the area, thereby decreasing risk[ 35 , 53 ]. Our analysis at the individual level did not show flooding to significantly increase or decrease the risk of dengue infection in the child cohorts in either country, perhaps reflecting this complexity. Interestingly though, when we considered flooding to be a settlement risk and evaluated the relationship between the degree of settlement flood exposure and settlement dengue prevalence, in Indonesia we found that settlements with more households experiencing flooding had fewer children with positive dengue serologies. Our findings support the hypothesis that flooding may flush out Ae. aegypti larva or reduce trash that support those larva[ 35 ], although given our small sample size, these findings should be interpreted cautiously. As extreme flooding increases with climate change, further studies are needed to better understand how flood microclimates affect Ae. aegypti proliferation and consequent disease risk. Finally, our study hints at the possibility that housing construction made of porous materials could be protective against dengue exposure. We had initially hypothesized that porous housing materials might let mosquitoes into the house which would increase risk. However porous housing construction could allow for increased ventilation and indoor lower temperatures, thereby decreasing the attractiveness of the home to Ae. aegypti mosquitoes which favor hot, humid environments. Porous flooring material was only found to decrease dengue risk significantly in univariate analysis in the Indonesia cohort. Porous walls were associated with a decrease which was not statistically significant in either model. Other studies have suggested that housing construction features that affect air flow modulate dengue risk[ 24 , 27 ]. More research is needed to further evaluate how porous housing materials may impact ventilation and indoor temperature and thus potentially lower mosquito burden. Our study is limited by arbovirus serology assay accuracy, particularly in the setting of multiple circulating arboviruses. Dengue and Zika are both flaviviruses with consequent potential for cross-reactivity on serology studies. However, since these viruses are transmitted by the same mosquitoes, in places with co-circulation, risk for one virus equates to risk for the other and prior infection with both viruses in some children would be expected. Using validated commercial ELISA kits, we ran all samples in duplicate and found complete concordance between duplicate runs; additionally, positive versus negative results separated clearly when evaluating titer values. We identified 1 individual in Indonesia and 3 individuals in Fiji who tested positive for Zika and negative for dengue; and the ratio of Zika to dengue positive results in the two countries was dissimilar. Based on these findings, we infer that at least some, if not all, of our Zika positive results were true positives. Chikungunya virus serology also has the potential to cross-react with other alphaviruses such as Ross River virus. Ross River virus is known to circulate in the broader region but is largely considered to cause asymptomatic infections, so prevalence is not well documented. Given these potential limitations with the Zika and chikungunya serologies and the relatively low prevalence, we elected not to estimate incidence or include them in the risk factor analysis. For all these viruses, there is also the potential for false positive results due to transfer of maternal antibodies. For this reason, we restricted sampling to children over 6 months of age, past the point of placental antibody transfer and often past the time for exclusive breastfeeding. Additionally, we found that breastfeeding rates at the time of serum sampling was low in both places, that breastfeeding children tested positive and negative on serology, and that breastfeeding was not associated with an increased likelihood of seropositivity. Therefore, we believe our results were not significantly impacted by the possibility of maternal antibody transfer. One limitation of our incidence estimates is that they are modeled based on seroprevalence and age, not measured by case counts. Unlike an acute febrile surveillance system, serology results cannot tell you when and where a case occurred. However, by testing very young children, we know that infection occurred during their relatively short lifespan and likely around their current residence. The other advantage of this approach to measuring incidence is that we can capture all infections, not only infections that resulted in symptomatic infection and diagnostic testing within a narrow detection window. One caveat though is that children in such a high incidence setting may have had multiple infections with different dengue serotypes, which would be missed by serology, resulting in an underestimate of incidence. However, this problem is more likely as children get older. Additionally, in places where childhood incidence is very high and infection results in lifelong immunity, the incidence in the adult population may be significantly lower than in the child population. Despite these limitations, estimations of recent dengue incidence in children more accurately reflects recent transmission dynamics and can be used to help monitor how disease transmission is changing. Finally, our risk factor analysis had some limitations. In Fiji we did not identify any built or natural environment risk factors for dengue infection. This may have been due to inadequate statistical power, relatively high or low rates of certain risk factors across the entire study population, or simply the extremely high burden of disease that obscured individual risk factors. A previous study in Fiji during a 2013–2014 dengue outbreak similarly did not identify any demographic or environmental risk factors for infection[ 44 ]. In Indonesia where dengue burden was lower and there was greater heterogeneity of key risk factors, such as trash collection, we did find that these factors contributed to dengue risk. We elected not to do a combined analysis of the Indonesia and Fiji data given the differences in seropositivity and various risk factors between these two countries. Self-reporting of risk factors, lack of information about neighbor practices that could affect the local environment, and unmeasured housing construction features in neighborhoods based on flood risk (i.e. housing built off the ground in flood-prone areas) are additional limitations of the risk factor analysis. We accounted for unmeasured neighborhood risk factors in our multivariable model by including settlement as a random effect and conducted a secondary analysis of overall settlement flooding and trash collection rates. Improved techniques to objectively measure environmental risk factors such as trash and flood exposure and housing design could improve our understanding of how these factors affect individual risk for arbovirus infection. Despite these limitations, we do see a strong effect of household trash disposal practices on infection risk in Indonesia and indications that flooding and housing construction affects risk and warrants further study. Conclusions In summary, our study found very high rates of dengue in young children living in informal urban settlements in Makassar, Indonesia and Suva, Fiji as well as lower rates of Zika and chikungunya in this population suggesting ongoing low-level transmission of these other two Ae. aegypti -transmitted viruses. Household trash collection and community flooding appear to be protective factors against dengue exposure. Further work to evaluate these modifiable risk factors and test interventions designed to disrupt transmission pathways can help mitigate the increasing risk of Ae. aegypti -transmitted viruses globally. Abbreviations RISE Revitalizing Informal Settlements and their Environment SD standard deviation IgG Immunoglobulin G OR odds ratio CI confidence interval Declarations Ethics approval and consent to participate : Ethics review and approval was provided by participating universities and local IRBs, including: Monash University Human Research Ethics Committee (Melbourne, Australia; project ID 35903), Ministry of Research, Technology and Higher Education Ethics Committee of Medical Research at the Faculty of Medicine, Universitas Hasanuddin (Makassar, Indonesia; protocol UH18020110), and Fiji National University College Human Health Research Ethics Committee (CHREC ID 137.19). All participants consented to participate in the study. Clinical Trial Number: Not applicable. Consent for publication : Not applicable. Availability of data and materials : At the end of the research trial, deidentified data will be stored on secure Monash infrastructure and made available, upon application, as approved by the ethics committees. Researchers interested in accessing data may contact the RISE Program (https://doi.org/10.26180/ctjf-vf69) Competing interests : None of the authors have any relevant conflict of interest or other financial disclosures relevant to the subject matter. Funding : This research was supported by NIH K32 AI168581 (JIR), ASTMH-Burroughs Wellcome Trust (JIR), Stanford Center for Innovation in Global Health Seed Grant (JIR). This research was part of the RISE program which is funded by the Wellcome Trust [grant 205222/Z/16/Z], the New Zealand Ministry of Foreign Affairs and Trade, the Australian Department of Foreign Affairs and Trade, the Government of Fiji, the Asian Development Bank and Monash University, and involves partnerships and in-kind contributions from the City of Makassar, the Cooperative Research Centre for Water Sensitive Cities (now Water Sensitive Cities Australia), Fiji National University, Hasanuddin University, Stanford University, Emory University, Melbourne University, Southeast Water, Melbourne Water, Live and Learn Environmental Education, UN-Habitat, UNU-IIGH, WaterAid International and Oxfam. Author Contributions : JIR conceived of the study design, led the laboratory work, verified and analyzed the data, and drafted the manuscript. JJO, AL, FB, RRT, and AT assisted with data acquisition. NT, NPEA, MA, and EB assisted with laboratory evaluations. KL, A, and IW supervised the project. All authors provided critical review of the manuscript. Acknowledgements: We would like to acknowledge the field and laboratory staff in Indonesia and Fiji, in particular Maghfira Saifuddaolah and Silivia Rosova-Vilsoni, and the RISE Consortium (https://doi.org/10.26180/ctjf-vf69). References Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496:504–7. Mordecai EA, Ryan SJ, Caldwell JM, Shah MM, LaBeaud AD. Climate change could shift disease burden from malaria to arboviruses in Africa. Lancet Planet Health. 2020;4:e416–23. Uddin KS, Ogden Nicholas H, Fazil Aamir A, Gachon Philippe H, Dueymes Guillaume U, Greer Amy L et al. Current and Projected Distributions of Aedes aegypti and Ae. albopictus in Canada and the U.S. Environ Health Perspect. 128:057007. Lowe R, Gasparrini A, Meerbeeck CJV, Lippi CA, Mahon R, Trotman AR, et al. Nonlinear and delayed impacts of climate on dengue risk in Barbados: A modelling study. PLOS Med. 2018;15:e1002613. Mordecai EA, Cohen JM, Evans MV, Gudapati P, Johnson LR, Lippi CA, et al. Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models. PLoS Negl Trop Dis. 2017;11:e0005568. Huber DG, Gulledge J. Extreme Weather and Climate Change: Understanding the Link, Managing the Risk. White Pap Sci Impacts Program. 2011. WHO. WHO | Global Strategy for dengue prevention and control, 2012–2020. 2012. https://www.who.int/denguecontrol/9789241504034/en/ . Accessed 27 Oct 2019. Labeaud AD, Bashir F, King CH. Measuring the burden of arboviral diseases: the spectrum of morbidity and mortality from four prevalent infections. Popul Health Metr. 2011;9:1. Silva MMO, Tauro LB, Kikuti M, Anjos RO, Santos VC, Gonçalves TSF, et al. Concomitant Transmission of Dengue, Chikungunya, and Zika Viruses in Brazil: Clinical and Epidemiological Findings From Surveillance for Acute Febrile Illness. Clin Infect Dis. 2019;69:1353–9. Ward C, Chapman J. Chikungunya in Children: A Clinical Review. Pediatr Emerg Care. 2018;34:510–5. Grossi-Soyster EN, LaBeaud AD. Clinical aspects of Zika virus. Curr Opin Pediatr. 2017;29:102–6. Puntasecca CJ, King CH, LaBeaud AD. Measuring the global burden of chikungunya and Zika viruses: A systematic review. PLoS Negl Trop Dis. 2021;15:e0009055. Krystosik A, Njoroge G, Odhiambo L, Forsyth JE, Mutuku F, LaBeaud AD. Solid Wastes Provide Breeding Sites, Burrows, and Food for Biological Disease Vectors, and Urban Zoonotic Reservoirs: A Call to Action for Solutions-Based Research. Front Public Health. 2020;7:405. Getachew D, Tekie H, Gebre-Michael T, Balkew M, Mesfin A. Breeding Sites of Aedes aegypti : Potential Dengue Vectors in Dire Dawa, East Ethiopia. Interdiscip Perspect Infect Dis. 2015;2015:1–8. Khan A, Bisanzio D, Mutuku F, Ndenga B, Grossi-Soyster EN, Jembe Z, et al. Spatiotemporal overlapping of dengue, chikungunya, and malaria infections in children in Kenya. BMC Infect Dis. 2023;23:183. Nosrat C, Altamirano J, Anyamba A, Caldwell JM, Damoah R, Mutuku F, et al. Impact of recent climate extremes on mosquito-borne disease transmission in Kenya. PLoS Negl Trop Dis. 2021;15:e0009182. Forsyth JE, Kempinsky A, Pitchik HO, Alberts CJ, Mutuku FM, Kibe L, et al. Larval source reduction with a purpose: Designing and evaluating a household- and school-based intervention in coastal Kenya. PLoS Negl Trop Dis. 2022;16:e0010199. Mwakutwaa AS, Ngugi HN, Ndenga BA, Krystosik A, Ngari M, Abubakar LU, et al. Pupal productivity of larval habitats of Aedes aegypti in Msambweni, Kwale County, Kenya. Parasitol Res. 2023;122:801–14. Forsyth JE, Mutuku FM, Kibe L, Mwashee L, Bongo J, Egemba C, et al. Source reduction with a purpose: Mosquito ecology and community perspectives offer insights for improving household mosquito management in coastal Kenya. PLoS Negl Trop Dis. 2020;14:e0008239. Ngugi HN, Mutuku FM, Ndenga BA, Musunzaji PS, Mbakaya JO, Aswani P, et al. Characterization and productivity profiles of Aedes aegypti (L.) breeding habitats across rural and urban landscapes in western and coastal Kenya. Parasit Vectors. 2017;10:331. Ngugi HN, Nyathi S, Krystosik A, Ndenga B, Mbakaya JO, Aswani P, et al. Risk factors for Aedes aegypti household pupal persistence in longitudinal entomological household surveys in urban and rural Kenya. Parasit Vectors. 2020;13:499. Sekhon DH, Minhas DS. A study of larval indices of Aedes and the risk for Dengue outbreak. Sch Acad J Biosci. 2014. Hayes JM, García-Rivera E, Flores-Reyna R, Suárez-Rangel G, Biggerstaff BJ, Rodríguez-Mata T, et al. Risk factors for infection during a severe dengue outbreak in El Salvador in 2000. Am J Trop Med Hyg. 2003;69:629–33. Gustave J, Fouque F, Cassadou S, Leon L, Anicet G, Ramdini C, et al. Increasing Role of Roof Gutters as Aedes aegypti (Diptera: Culicidae) Breeding Sites in Guadeloupe (French West Indies) and Consequences on Dengue Transmission and Vector Control. J Trop Med. 2012;2012:249524. Trewin BJ, Darbro JM, Zalucki MP, Jansen CC, Schellhorn NA, Devine GJ. Life on the margin: Rainwater tanks facilitate overwintering of the dengue vector, Aedes aegypti, in a sub-tropical climate. PLoS ONE. 2019;14:e0211167. Sukiato F, Wasserman RJ, Foo SC, Wilson RF, Cuthbert RN. The effects of temperature and shading on mortality and development rates of Aedes aegypti (Diptera: Culicidae). J Vector Ecol J Soc Vector Ecol. 2019;44:264–70. Lippi CA, Stewart-Ibarra AM, Endy TP, Abbott M, Cueva C, Heras F, et al. Exploring the utility of social-ecological and entomological risk factors for dengue infection as surveillance indicators in the dengue hyper-endemic city of Machala, Ecuador. PLoS Negl Trop Dis. 2021;15:e0009257. Kohn M. Occurrence of Aedes aegypti (L.) and Culex quinquefasciatus Say (Diptera, Culicidae) in houses of different constructions in Phnom Penh, Kampuchea. Folia Parasitol (Praha). 1991;38:75–8. Manrique-Saide P, Herrera-Bojórquez J, Villegas-Chim J, Puerta-Guardo H, Ayora-Talavera G, Parra-Cardeña M, et al. Protective effect of house screening against indoor Aedes aegypti in Mérida, Mexico: A cluster randomised controlled trial. Trop Med Int Health TM IH. 2021;26:1677–88. Baker JL, Gadgil GU. East Asia and Pacific Cities: Expanding Opportunities for the Urban Poor. Washington, DC: World Bank; 2017. Mavian C, Dulcey M, Munoz O, Salemi M, Vittor AY, Capua I. Islands as Hotspots for Emerging Mosquito-Borne Viruses: A One-Health Perspective. Viruses. 2018;11. Prayitno A, Taurel A-F, Nealon J, Satari HI, Karyanti MR, Sekartini R, et al. Dengue seroprevalence and force of primary infection in a representative population of urban dwelling Indonesian children. PLoS Negl Trop Dis. 2017;11:e0005621. Mordecai EA, Caldwell JM, Grossman MK, Lippi CA, Johnson LR, Neira M, et al. Thermal biology of mosquito-borne disease. Ecol Lett. 2019;22:1690–708. Hii YL, Zhu H, Ng N, Ng LC, Rocklöv J. Forecast of Dengue Incidence Using Temperature and Rainfall. PLoS Negl Trop Dis. 2012;6:e1908. Caldwell JM, LaBeaud AD, Lambin EF, Stewart-Ibarra AM, Ndenga BA, Mutuku FM, et al. Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents. Nat Commun. 2021;12:1233. Rodysill JR, Russell JM, Vuille M, Dee S, Lunghino B, Bijaksana S. La Niña-driven flooding in the Indo-Pacific warm pool during the past millennium. Quat Sci Rev. 2019;225:106020. Ummenhofer CC, D’Arrigo RD, Anchukaitis KJ, Buckley BM, Cook ER. Links between Indo-Pacific climate variability and drought in the Monsoon Asia Drought Atlas. Clim Dyn. 2013;40:1319–34. Statistics Indonesia. Statistical Yearbook of Indonesia 2014. Statistics Indonesia; 2014. Leder K, Openshaw JJ, Allotey P, Ansariadi A, Barker SF, Burge K, et al. Study design, rationale and methods of the Revitalising Informal Settlements and their Environments (RISE) study: a cluster randomised controlled trial to evaluate environmental and human health impacts of a water-sensitive intervention in informal settlements in Indonesia and Fiji. BMJ Open. 2021;11:e042850. Whitaker HJ, Farrington CP. Estimation of infectious disease parameters from serological survey data: the impact of regular epidemics. Stat Med. 2004;23:2429–43. Tedijanto C, Solomon AW, Martin DL, Nash SD, Keenan JD, Lietman TM, et al. Monitoring transmission intensity of trachoma with serology. Nat Commun. 2023;14:3269. Sasmono RT, Taurel A-F, Prayitno A, Sitompul H, Yohan B, Hayati RF, et al. Dengue virus serotype distribution based on serological evidence in pediatric urban population in Indonesia. PLoS Negl Trop Dis. 2018;12:e0006616. Sasmono RT, Johar E, Yohan B, Ma’roef CN, Pronyk P, Hadinegoro SR, et al. Spatiotemporal Heterogeneity of Zika Virus Transmission in Indonesia: Serosurveillance Data from a Pediatric Population. Am J Trop Med Hyg. 2021;104:2220–3. Kucharski AJ, Kama M, Watson CH, Aubry M, Funk S, Henderson AD et al. Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji. eLife. 7. Matthews RJ, Kaluthotage I, Russell TL, Knox TB, Horwood PF, Craig AT. Arboviral Disease Outbreaks in the Pacific Islands Countries and Areas, 2014 to 2020: A Systematic Literature and Document Review. Pathogens. 2022;11:74. Moore TC, Brown HE. Estimating Aedes aegypti (Diptera: Culicidae) Flight Distance: Meta-Data Analysis. J Med Entomol. 2022;59:1164–70. Banerjee S, Aditya G, Saha GK. Household disposables as breeding habitats of dengue vectors: Linking wastes and public health. Waste Manag. 2013;33:233–9. Banerjee S, Aditya G, Saha GK. Household Wastes as Larval Habitats of Dengue Vectors: Comparison between Urban and Rural Areas of Kolkata, India. PLoS ONE. 2015;10:e0138082. Dieng H, Satho T, Meli NKKB, Abang F, Nolasco-Hipolito C, Hakim H, et al. Occurrence of sweet refuse at disposal sites: rainwater retention capacity and potential breeding opportunities for Aedes aegypti. Environ Sci Pollut Res Int. 2018;25:13833–43. Shaikh OA, Baig MT, Tahir S, Parekh A-DE, Nashwan AJ. Dengue outbreak following unprecedented flooding in Pakistan. Hyg Environ Health Adv. 2023;7:100076. UNICEF Peru Flash Update No. 1 (Flooding and Dengue Outbreak) – 01 Dec 2023–01 March 2024 - Peru | ReliefWeb. 2024. https://reliefweb.int/report/peru/unicef-peru-flash-update-no-1-flooding-and-dengue-outbreak-01-dec-2023-01-march-2024 . Accessed 16 Jul 2024. Post-Flood Dengue Outbreak Puts UAE Migrant Workers at Heightened Risk. – FairSquare. https://fairsq.org/post-flood-dengue-outbreak-puts-uae-migrant-workers-at-heightened-risk/ . Accessed 16 Jul 2024. Coalson JE, Anderson EJ, Santos EM, Madera Garcia V, Romine JK, Dominguez B, et al. The Complex Epidemiological Relationship between Flooding Events and Human Outbreaks of Mosquito-Borne Diseases: A Scoping Review. Environ Health Perspect. 2021;129:96002. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5141509","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":359212877,"identity":"2253da47-41b8-4337-b312-46521fd81c1a","order_by":0,"name":"Joelle I. 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Dengue virus is the most common arbovirus globally, has increased exponentially over the last several decades[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and causes an acute febrile illness with clinical presentations ranging from asymptomatic to life-threatening hemorrhage and shock[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. While less prevalent than dengue, chikungunya and Zika viruses have also emerged as global problems over recent decades and can cause long term morbidity[\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs the climate continues to change, generating reliable estimates of infection rates for \u003cem\u003eAe. aegypti\u003c/em\u003e transmitted viral infections is essential to monitoring changing transmission dynamics and generating models to forecast future risk. Current estimates of recent disease transmission are limited by a reliance on acute febrile surveillance and cross-sectional serology studies in the general population. Acute febrile surveillance underreports the true burden of disease, only tracking cases that come to the hospital and receive a correct diagnosis. Dengue, chikungunya, and Zika infections all have non-specific clinical presentations; and diagnostic tests for infections are not readily available in many medical systems and have a limited window for detection. Furthermore, surveillance reporting requirements and resources can vary between locations and over time. An alternative to acute febrile surveillance is estimating disease burden with cross-sectional serology studies. Seroprevalence studies are also limited in that a positive serology indicates any past infection, not just recent infection, and antibody levels wane over time. However, in places with a high incidence of disease, serology studies performed in young children can overcome these limitations and provide insights into recent disease incidence.\u003c/p\u003e \u003cp\u003eWhile climate change may be fueling the spread of \u003cem\u003eAe. aegypti-\u003c/em\u003etransmitted viruses, local environmental factors can also affect an individual\u0026rsquo;s risk of exposure. \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes breed in small containers of fresh water, including water storage containers, trash, discarded tires, and gutters on houses that fill with rainwater[\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Local conditions, including temperature, humidity, and air circulation, also affect where the adult mosquitoes reside[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The role of the built environment, such as housing construction[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and landscaping[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], in modulating dengue risk is beginning to be recognized. As climate change exacerbates \u003cem\u003eAe. aegypti\u003c/em\u003e-transmitted viruses, there is a critical need for better understanding modifiable features of the built environment that attenuate transmission risk and can be targets for local interventions.\u003c/p\u003e \u003cp\u003eInformal urban settlements in Indonesia and Fiji have known high rates of dengue infection[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The hot, humid climate is highly suitable for the \u003cem\u003eAe. aegypti\u003c/em\u003e lifecycle and virus incubation[\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Fluctuations between drought and flooding in the region[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and inadequate water infrastructure[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] in the settlements results in pooling of rainwater during heavy rains and storage of water during dry periods, both providing breeding grounds for \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes. Inadequate trash management can additionally provide containers for mosquito oviposition[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe objectives of this study are to measure seroprevalence and estimate the incidence of dengue, chikungunya, and Zika infections in young children living in informal urban settlements in Indonesia and Fiji. This study also aims to evaluate local environmental risk factors for \u003cem\u003eAe. aegypti\u003c/em\u003e \u0026ndash; transmitted arbovirus infections.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cstrong\u003eStudy Population\u003c/strong\u003e \u003cp\u003eThe Revitalizing Informal Settlements and their Environment (RISE) study was conducted in 24 informal urban settlements in Makassar, Indonesia and Suva, Fiji with enrollment and study procedures previously described[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This study involved questionnaires and biological sampling of children between the ages of 6 months to 5 years old living in the RISE sites in 2018 and 2019 who were enrolled in the study and whose parents consented for their participation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eQuestionnaires\u003c/strong\u003e \u003cp\u003eBaseline questionnaires were used to assess household and individual demographic information and environmental exposures that were hypothesized to be predictive of dengue, chikungunya, and Zika seropositivity.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSerology testing\u003c/strong\u003e \u003cp\u003eWe performed dengue, chikungunya, and Zika virus serology testing on serum samples collected from children under 5 years old enrolled in the RISE study who underwent sampling in 2018 in Indonesia and in 2019 in both Indonesia and Fiji. Serum samples were stored in Sarstedt screw cap tubes at -80\u0026deg;C for four years prior to serology testing. Serology testing was performed in duplicate using Abcam IgG ELISA\u0026rsquo;s kits to evaluate for evidence of prior exposure to dengue, chikungunya, and Zika viruses. Duplicate positive, negative, and cut-off controls were used on each plate. Following Abcam kit protocols, antibody titers were converted into standard units based on average cut-off values and all samples with titers greater than 10 standard units were considered positive. Seropositivity rates are reported for each arbovirus and for the proportion of children with evidence of multiple prior infections.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIncidence estimates\u003c/strong\u003e \u003cp\u003eCatalytic models estimate the force of primary infection, or incidence rate, using seroprevalence data in diseases where seroprevalence is a marker of any past infection and indicates lifelong immunity[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Dengue infection, particularly in young children, meets these criteria and catalytic models have previously been used to estimate dengue incidence[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Using a catalytic model, we estimated dengue incidence in each country assuming a constant force of infection over time whereby \u003cem\u003eincidence\u0026thinsp;=\u0026thinsp;1\u0026ndash;(1\u0026ndash;seroprevalence)^(1/ mean years of exposure)\u003c/em\u003e.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRisk factor analysis\u003c/strong\u003e \u003cp\u003eBaseline demographic and environmental risk factors for dengue infection in the children enrolled in the RISE study were evaluated by a univariate logistic regression model and a multivariable logistic regression accounting for settlement as a fixed effect and individual characteristics thought to be plausible risk factors for dengue as random effects. For the two breastfeeding questions, \u0026ldquo;breastfeeding currently\u0026rdquo; was retained in the multivariable model since it was significant in the univariate model in Fiji; however, a sensitivity analysis was also performed which replaced \u0026ldquo;breastfed in the past 3 months\u0026rdquo; in the model, which did not change the findings.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eAs a further exploration of the potential impact of household variables that might have an impact on the surrounding settlement arbovirus exposure risk \u0026ndash; namely flooding and trash collection - we also conducted univariate linear regression at the settlement level to evaluate whether the proportion of households reporting flooding and trash collection were predictive of dengue seropositivity across the settlement. This settlement analysis was restricted to settlements with at least 10 children tested and multivariable regression was not conducted given the small sample size.\u003c/p\u003e \u003cp\u003eAll risk factor analyses were conducted to evaluate risk of dengue infection. Given the overall low chikungunya and Zika seroprevalence and the fact that the majority of individuals with evidence of either of these two infections were seropositive for dengue, risk factor assessment was not conducted for these other viruses. All analyses were performed in R version 2023.06.1.\u003c/p\u003e \u003cp\u003e\u003cem\u003eEthics\u003c/em\u003e: Ethics review and approval was provided by participating universities and local IRBs, including: Monash University Human Research Ethics Committee (Melbourne, Australia; project ID 35903), Ministry of Research, Technology and Higher Education Ethics Committee of Medical Research at the Faculty of Medicine, Universitas Hasanuddin (Makassar, Indonesia; protocol UH18020110), and Fiji National University College Human Health Research Ethics Committee (CHREC ID 137.19). This trial is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12618000633280; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.anzctr.org.au/\u003c/span\u003e\u003cspan address=\"https://www.anzctr.org.au/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cstrong\u003eDemographic Characteristics\u003c/strong\u003e \u003cp\u003eA total of 191 children in Fiji and 181 children in Indonesia were included in the study. Overall, the mean age of children at the time of serum sample collection was 3.3 years old and male children comprised 61% of the study population. Breastfeeding, household trash collection, having a household member who grows plants, and porous building materials for household construction was more commonly reported amongst participants in Fiji than Indonesia. In contrast, flooding in or around the house was more commonly reported in Indonesia. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of children in Fiji and Indonesia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFiji \u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;191)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndonesia \u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;181)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChild characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107/191 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119/181 (66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge: mean (sd)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreastfed in the past 3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50/185 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20/181 (11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreastfeeding currently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35/185 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17/181 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEthnicity \u0026amp; religion of household respondent\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEthnicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-Taukei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168/189 (89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndo Fijian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11/189 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Fijian or Mixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10/189 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMakassar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108/163 (66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBugis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11/163 (7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eToraja\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/163 (5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Indonesian or Mixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36/163 (22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eReligion\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76/189 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLotu Vakarisito\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101/189 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther or Mixed (Fiji)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12/189 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152/163 (93%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther or Mixed (Indonesia)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11/163 (7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHousehold characteristics\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReports many mosquito bites\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156/191 (82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151/160 (94%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold trash collection\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161/191 (84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103/160 (64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrows plants\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126/191 (66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79/160 (49%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperiences flooding in or outside the house\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52/191 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86/181 (48%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlooring made of porous material\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182/191 (95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53/160 (33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWalls made of porous material\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84/191 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37/160 (23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStores water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145/191 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146/160 (91%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: sd\u0026thinsp;=\u0026thinsp;standard deviation\u003c/p\u003e \u003cp\u003eIn Fiji, there were 2 children with missing data on ethnicity and religion and 6 children with missing data on breastfeeding status. In Indonesia, there were 21 children with missing data on various household characteristics.\u003c/p\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eHousehold respondent reported that in the past 6 weeks they experienced mosquitoes biting inside the house at least several times a week.\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eTrash is always collected and taken away or taken to a neighborhood collection point.\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eA household member grows plants in the house, garden, or settlement croplands.\u003c/p\u003e \u003cp\u003e\u003csup\u003e4\u003c/sup\u003ePorous housing material included wood, bamboo, woven mat, dirt, and tent material; in contrast, non-porous materials included cement, ceramic tiles, bricks, laminate, granite, and metal.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSeropositivity\u003c/strong\u003e \u003cp\u003eDengue IgG seropositivity was high in both countries, with 46% of children in Fiji and 33% of children in Indonesia demonstrating evidence of prior dengue exposure. Zika seropositivity was higher in Fiji than Indonesia. Chikungunya seropositivity was low but detectable in both countries. A total of 19 children (10%) in Fiji and 7 children (3%) in Indonesia were seropositive for more than one arbovirus. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIgG Seropositivity of Aedes-transmitted arboviruses in children under 5 years old\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArbovirus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFiji \u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;191)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndonesia \u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;181)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAll results\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDengue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (46.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChikungunya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZika\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMultiple infections\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDengue \u0026amp; Chikungunya\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDengue \u0026amp; Zika\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDengue \u0026amp; Chikungunya \u0026amp; Zika\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: IgG\u0026thinsp;=\u0026thinsp;Immunoglobulin G.\u003c/p\u003e \u003cp\u003e\"All results\" includes all children who tested positive on IgG ELISA for each arbovirus, regardless of results of the other serology tests. \"Multiple infections\" refers to the number of children who tested positive on multiple serology tests, indicating infection with multiple arboviruses during their lifetime, although not necessarily co-infection at the same time.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDengue seropositivity overall increased with age, with the exception of the 0.5 to \u0026lt;\u0026thinsp;1 year olds which showed a relatively high seropositivity but had very low numbers of participants. By the age of 4 to 5 years old, 71% and 51% of the children in Fiji and Indonesia respectively had been infected with dengue (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Using a catalytic model, we estimated an annual incidence rate of 18% in Fiji and 11% in Indonesia. Although seroprevalence rates of chikungunya and Zika were too low to model incidence, seropositivity was found in multiple age groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDengue seropositivity by age\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFiji\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;191\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndonesia\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;181\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.5 to \u0026lt;\u0026thinsp;1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/10 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/3 (33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to \u0026lt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2/28 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/17 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 to \u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10/37 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/36 (25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 to \u0026lt;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33/57 (58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14/58 (24%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 to \u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42/59 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34/67 (51%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDengue risk increases with age in both countries, consistent with continuous increasing exposure over time. This is consistent with endemic transmission rather than a single epidemic. \u003c/p\u003e \u003cp\u003e*Seroprevalence estimates may be artificially elevated for this age category because this only includes children\u0026thinsp;\u0026gt;\u0026thinsp;6 months, not across the entire range. Estimates in this group are also less precise due to small sample size in this group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eDemographic and environmental risk factors for dengue\u003c/em\u003e: Age was a significant predictor of dengue serostatus amongst children in Fiji and Indonesia in both unadjusted and adjusted models [Adjusted models - Fiji: OR 4.0 (95% CI: 2.5\u0026ndash;6.3); Indonesia: OR 2.2 (95% CI: 1.4\u0026ndash;3.6)]. In Indonesia, children living in a household with trash collection were significantly less likely to be dengue seropositive in both unadjusted and adjusted models [Adjusted model OR 0.3 (95% CI: 0.1\u0026ndash;0.8)]. Living in a house made of porous flooring material was also protective against dengue exposure amongst children in Indonesia, although this was only significant in the unadjusted model [OR 0.4 (95% CI: 0.2\u0026ndash;0.9)]. In Fiji, children who were currently breastfeeding at the time of serum sampling were less likely to be seropositive for dengue in the unadjusted model [OR 0.3 (95% CI: 0.1\u0026ndash;0.7)], but this did not remain statistically significant in the adjusted model accounting for age. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) Household flooding was not a significant predictor of individual dengue seropositivity in Indonesia or Fiji; however, in Indonesia, settlements with a higher proportion of households reporting flooding had lower rates of dengue. (Figure)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and environmental risk factors for dengue exposure amongst children in Fiji and Indonesia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eFiji\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eIndonesia\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative (N\u0026thinsp;=\u0026thinsp;103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive (N\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnadjusted Model \u003c/p\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted Model \u003c/p\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNegative (N\u0026thinsp;=\u0026thinsp;122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive (N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUnadjusted Model \u003c/p\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAdjusted Model \u003c/p\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.6\u0026ndash;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9 (0.4\u0026ndash;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36 (61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.7 (0.4\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.9 (0.4\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.9 (2.1\u0026ndash;4.1) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4.0 (2.5\u0026ndash;6.3)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.9 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2.0 (1.4\u0026ndash;2.9) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e2.2 (1.4\u0026ndash;3.6)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreastfed in the past 3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33/102 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17/83 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (0.3\u0026ndash;1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7 (1\u0026ndash;7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.3 (0.1\u0026ndash;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.7 (0.1\u0026ndash;3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreastfeeding currently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27/102 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/83 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.3 (0.1\u0026ndash;0.7) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u0026nbsp;(0.5\u0026ndash;4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4 (0.1\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.9\u0026nbsp;(0.2\u0026ndash;4.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReports many mosquito bites\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4 (0.6\u0026ndash;2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6 (0.2\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e104/111 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47/49 (96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.6 (0.4\u0026ndash;10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.3 (0.5\u0026ndash;21.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold trash collection\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86 (83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.5\u0026ndash;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2 (0.7\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79/111 (71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24/49 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.4 (0.2\u0026ndash;0.8) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.3 (0.1\u0026ndash;0.8)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrows plants\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3 (0.7\u0026ndash;2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.3 (0.6\u0026ndash;3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54/111 (49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25/49 (51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.1 (0.6\u0026ndash;2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1 (0.5\u0026ndash;2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExperiences flooding in or outside the house\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.6\u0026ndash;2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5 (0.2\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.9 (0.5\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6 (0.7\u0026ndash;3.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlooring made of porous material\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 (97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8 (0.4\u0026ndash;8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5 (0.4\u0026ndash;15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43/111 (39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10/49 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.4 (0.2\u0026ndash;0.9) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.4 (0.2\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWalls made of porous material\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9 (0.5\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8 (0.3\u0026ndash;1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28/111 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9/49 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.7 (0.3\u0026ndash;1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.0 (0.4\u0026ndash;2.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStores water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.5\u0026ndash;2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9 (0.4\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101/111 (92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45/49 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.8 (0.3\u0026ndash;2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.5 (0.1\u0026ndash;2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: OR\u0026thinsp;=\u0026thinsp;odds ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval\u003c/p\u003e \u003cp\u003e\u003cb\u003e*\u003c/b\u003eIndicates statistically significant result with a threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003eDenominators provided for all variables with missing data.\u003c/p\u003e \u003cp\u003eIn the adjusted models, we ran a second model for breastfeeding currently that excluded breastfed in the past 3 months and a second model for flooring and walls made of porous material that excluded the individual variables for flooring and walls.\u003c/p\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eHousehold respondent reported that in the past 6 weeks they experienced mosquitoes biting inside the house at least several times a week.\u003c/p\u003e \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eTrash is always collected and taken away or taken to a neighborhood collection point\u003c/p\u003e \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eA household member grows plants in the house, garden, or settlement croplands.\u003c/p\u003e \u003cp\u003e\u003csup\u003e4\u003c/sup\u003ePorous housing material included wood, bamboo, woven mat, dirt, and tent material; in contrast, non-porous materials included cement, ceramic tiles, bricks, laminate, granite, and metal.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure. Settlement level dengue seropositivity versus flooding and trash collection rates\u003c/p\u003e \u003cp\u003e*Indicates statistically significant result with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSettlements in Indonesia with a higher percentage of houses that reported flooding in or around their house had significantly lower dengue seropositivity rates, suggestive that flooding could reduce breeding habitats.\u003c/p\u003e \u003cp\u003eSettlements in both Fiji and Indonesia with a higher percentage of houses reporting trash collection seem to have lower dengue seropositivity rates, consistent with the individual level analysis, but this was not found to be significant at the settlement level. In Fiji, trash collection was found to be high across most settlements, making any potential correlation to dengue risk difficult to ascertain.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study found a high prevalence of dengue in Fiji and Indonesia, with over half of children in each country having had an infection by the age of five years old. Although chikungunya and Zika exposure was lower, a seroprevalence of 2\u0026ndash;9% in such young children suggests ongoing transmission of these other \u003cem\u003eAe. aegypti \u0026ndash;\u003c/em\u003e transmitted viruses in these countries as well.\u003c/p\u003e \u003cp\u003eOur dengue seroprevalence estimates are similar to those found in a 2014 study of urban children across Indonesia[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and in South Sulawesi in particular[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], corroborating the high rates of dengue in Indonesia. Although dengue circulation in Fiji is well established with many known outbreaks over the years, dengue seroprevalence and incidence data across Fiji is limited[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our study is one of the few studies providing such estimates and showed high circulation of dengue in Suva, the capital city located in the Central District of the Island of Vitu Levi. Our study also showed a steady increase in seropositivity for each year of age in children under 5 years old in both countries, indicating high levels of non-epidemic transmission.\u003c/p\u003e \u003cp\u003eOther studies in Indonesia and Fiji looking at demographic or environmental risk factors have not identified significant risk factors for dengue seropositive test results[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Our study focused on environmental features of the built environment that would be expected to increase dengue exposure and looked at the youngest children as they acquire their first dengue infections, thus giving a potentially unique window into risk factors in places with very high levels of risk.\u003c/p\u003e \u003cp\u003eTrash being collected and removed from the household in our cohort in Indonesia was a significant protective factor against dengue infection in the individual level analysis. In the secondary analysis at the settlement level, we observe a similar correlation between settlement trash collection and settlement dengue risk. Although the settlement level analysis was not found to be statistically significantly, we suspect this is due to inadequate statistical power with this small sample size or that household practices are a stronger driver of risk given the relatively short flight range of \u003cem\u003eAe. aegypti.\u003c/em\u003e We did not find a significant association between trash collection and dengue in the Fiji cohort in either the individual or community level analyses. In Fiji, the higher overall dengue risk may overwhelm such individual environmental risk; furthermore, trash collection was very common (83%) in Fiji, diminishing our power to detect a difference in dengue exposure in this cohort. \u003cem\u003eAe. aegypti\u003c/em\u003e breed in small containers of water[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and have a relatively short range of about 100 meters[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Our findings in Indonesia corroborate other studies demonstrating \u003cem\u003eAe. aegypti\u003c/em\u003e breeding in trash filled with rainwater [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and implicate household trash disposal practices as a dengue exposure risk. Our study adds to the existing literature not only by showing this direct association between household trash disposal practices and individual disease risk but also by highlighting the risk posed by inadequate trash collection in informal settlements. Because they are not legally recognized neighborhoods, informal settlements are often excluded from government trash collection programs, particularly in Makassar, Indonesia. Our study indicates that household trash removal could decrease disease exposure and endorses the inclusion of informal settlements in regular government trash collection programs.\u003c/p\u003e \u003cp\u003eThe impact of flooding on dengue risk is complex and remains poorly understood. While dengue outbreaks following large floods frequently make news headlines[\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], it is unclear whether these outbreaks are due to the floods themselves, heavy rainfall regardless of flooding, or an extended duration of pooled water as floodwaters recede. Other studies have proposed that while heavy rainfall fills up potential \u003cem\u003eAe. aegypti\u003c/em\u003e breeding grounds with water, severe flooding may in fact flush out those small containers holding water and \u003cem\u003eAe. aegypti\u003c/em\u003e larva, or wash away trash containers from the area, thereby decreasing risk[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Our analysis at the individual level did not show flooding to significantly increase or decrease the risk of dengue infection in the child cohorts in either country, perhaps reflecting this complexity. Interestingly though, when we considered flooding to be a settlement risk and evaluated the relationship between the degree of settlement flood exposure and settlement dengue prevalence, in Indonesia we found that settlements with more households experiencing flooding had fewer children with positive dengue serologies. Our findings support the hypothesis that flooding may flush out \u003cem\u003eAe. aegypti\u003c/em\u003e larva or reduce trash that support those larva[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], although given our small sample size, these findings should be interpreted cautiously. As extreme flooding increases with climate change, further studies are needed to better understand how flood microclimates affect \u003cem\u003eAe. aegypti\u003c/em\u003e proliferation and consequent disease risk.\u003c/p\u003e \u003cp\u003eFinally, our study hints at the possibility that housing construction made of porous materials could be protective against dengue exposure. We had initially hypothesized that porous housing materials might let mosquitoes into the house which would increase risk. However porous housing construction could allow for increased ventilation and indoor lower temperatures, thereby decreasing the attractiveness of the home to \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes which favor hot, humid environments. Porous flooring material was only found to decrease dengue risk significantly in univariate analysis in the Indonesia cohort. Porous walls were associated with a decrease which was not statistically significant in either model. Other studies have suggested that housing construction features that affect air flow modulate dengue risk[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. More research is needed to further evaluate how porous housing materials may impact ventilation and indoor temperature and thus potentially lower mosquito burden.\u003c/p\u003e \u003cp\u003eOur study is limited by arbovirus serology assay accuracy, particularly in the setting of multiple circulating arboviruses. Dengue and Zika are both flaviviruses with consequent potential for cross-reactivity on serology studies. However, since these viruses are transmitted by the same mosquitoes, in places with co-circulation, risk for one virus equates to risk for the other and prior infection with both viruses in some children would be expected. Using validated commercial ELISA kits, we ran all samples in duplicate and found complete concordance between duplicate runs; additionally, positive versus negative results separated clearly when evaluating titer values. We identified 1 individual in Indonesia and 3 individuals in Fiji who tested positive for Zika and negative for dengue; and the ratio of Zika to dengue positive results in the two countries was dissimilar. Based on these findings, we infer that at least some, if not all, of our Zika positive results were true positives. Chikungunya virus serology also has the potential to cross-react with other alphaviruses such as Ross River virus. Ross River virus is known to circulate in the broader region but is largely considered to cause asymptomatic infections, so prevalence is not well documented. Given these potential limitations with the Zika and chikungunya serologies and the relatively low prevalence, we elected not to estimate incidence or include them in the risk factor analysis.\u003c/p\u003e \u003cp\u003eFor all these viruses, there is also the potential for false positive results due to transfer of maternal antibodies. For this reason, we restricted sampling to children over 6 months of age, past the point of placental antibody transfer and often past the time for exclusive breastfeeding. Additionally, we found that breastfeeding rates at the time of serum sampling was low in both places, that breastfeeding children tested positive and negative on serology, and that breastfeeding was not associated with an increased likelihood of seropositivity. Therefore, we believe our results were not significantly impacted by the possibility of maternal antibody transfer.\u003c/p\u003e \u003cp\u003eOne limitation of our incidence estimates is that they are modeled based on seroprevalence and age, not measured by case counts. Unlike an acute febrile surveillance system, serology results cannot tell you when and where a case occurred. However, by testing very young children, we know that infection occurred during their relatively short lifespan and likely around their current residence. The other advantage of this approach to measuring incidence is that we can capture all infections, not only infections that resulted in symptomatic infection and diagnostic testing within a narrow detection window. One caveat though is that children in such a high incidence setting may have had multiple infections with different dengue serotypes, which would be missed by serology, resulting in an underestimate of incidence. However, this problem is more likely as children get older. Additionally, in places where childhood incidence is very high and infection results in lifelong immunity, the incidence in the adult population may be significantly lower than in the child population. Despite these limitations, estimations of recent dengue incidence in children more accurately reflects recent transmission dynamics and can be used to help monitor how disease transmission is changing.\u003c/p\u003e \u003cp\u003eFinally, our risk factor analysis had some limitations. In Fiji we did not identify any built or natural environment risk factors for dengue infection. This may have been due to inadequate statistical power, relatively high or low rates of certain risk factors across the entire study population, or simply the extremely high burden of disease that obscured individual risk factors. A previous study in Fiji during a 2013\u0026ndash;2014 dengue outbreak similarly did not identify any demographic or environmental risk factors for infection[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In Indonesia where dengue burden was lower and there was greater heterogeneity of key risk factors, such as trash collection, we did find that these factors contributed to dengue risk. We elected not to do a combined analysis of the Indonesia and Fiji data given the differences in seropositivity and various risk factors between these two countries. Self-reporting of risk factors, lack of information about neighbor practices that could affect the local environment, and unmeasured housing construction features in neighborhoods based on flood risk (i.e. housing built off the ground in flood-prone areas) are additional limitations of the risk factor analysis. We accounted for unmeasured neighborhood risk factors in our multivariable model by including settlement as a random effect and conducted a secondary analysis of overall settlement flooding and trash collection rates. Improved techniques to objectively measure environmental risk factors such as trash and flood exposure and housing design could improve our understanding of how these factors affect individual risk for arbovirus infection. Despite these limitations, we do see a strong effect of household trash disposal practices on infection risk in Indonesia and indications that flooding and housing construction affects risk and warrants further study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, our study found very high rates of dengue in young children living in informal urban settlements in Makassar, Indonesia and Suva, Fiji as well as lower rates of Zika and chikungunya in this population suggesting ongoing low-level transmission of these other two \u003cem\u003eAe. aegypti\u003c/em\u003e-transmitted viruses. Household trash collection and community flooding appear to be protective factors against dengue exposure. Further work to evaluate these modifiable risk factors and test interventions designed to disrupt transmission pathways can help mitigate the increasing risk of \u003cem\u003eAe. aegypti\u003c/em\u003e-transmitted viruses globally.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRISE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRevitalizing Informal Settlements and their Environment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIgG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunoglobulin G\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eEthics review and approval was provided by participating universities and local IRBs, including: Monash University Human Research Ethics Committee (Melbourne, Australia; project ID 35903), Ministry of Research, Technology and Higher Education Ethics Committee of Medical Research at the Faculty of Medicine, Universitas Hasanuddin (Makassar, Indonesia; protocol UH18020110), and Fiji National University College Human Health Research Ethics Committee (CHREC ID 137.19). All participants consented to participate in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical Trial Number:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAt the end of the research trial, deidentified data will be stored on secure Monash infrastructure and made available, upon application, as approved by the ethics committees. Researchers interested in accessing data may contact the RISE Program (https://doi.org/10.26180/ctjf-vf69)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eNone of the authors have any relevant conflict of interest or other financial disclosures relevant to the subject matter.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThis research was supported by NIH K32 AI168581 (JIR), ASTMH-Burroughs Wellcome Trust (JIR), Stanford Center for Innovation in Global Health Seed Grant (JIR). This research was part of the RISE program which is funded by the Wellcome Trust [grant 205222/Z/16/Z], the New Zealand Ministry of Foreign Affairs and Trade, the Australian Department of Foreign Affairs and Trade, the Government of Fiji, the Asian Development Bank and Monash University, and involves partnerships and in-kind contributions from the City of Makassar, the Cooperative Research Centre for Water Sensitive Cities (now Water Sensitive Cities Australia), Fiji National University, Hasanuddin University, Stanford University, Emory University, Melbourne University, Southeast Water, Melbourne Water, Live and Learn Environmental Education, UN-Habitat, UNU-IIGH, WaterAid International and Oxfam.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contributions\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eJIR conceived of the study design, led the laboratory work, verified and analyzed the data, and drafted the manuscript. JJO, AL, FB, RRT, and AT assisted with data acquisition. NT, NPEA, MA, and EB assisted with laboratory evaluations. KL, A, and IW supervised the project. All authors provided critical review of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements:\u003c/em\u003e\u003c/strong\u003eWe would like to acknowledge the field and laboratory staff in Indonesia and Fiji, in particular Maghfira Saifuddaolah and Silivia Rosova-Vilsoni, and the RISE Consortium (https://doi.org/10.26180/ctjf-vf69). \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496:504\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMordecai EA, Ryan SJ, Caldwell JM, Shah MM, LaBeaud AD. Climate change could shift disease burden from malaria to arboviruses in Africa. Lancet Planet Health. 2020;4:e416\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUddin KS, Ogden Nicholas H, Fazil Aamir A, Gachon Philippe H, Dueymes Guillaume U, Greer Amy L et al. Current and Projected Distributions of Aedes aegypti and Ae. albopictus in Canada and the U.S. Environ Health Perspect. 128:057007.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLowe R, Gasparrini A, Meerbeeck CJV, Lippi CA, Mahon R, Trotman AR, et al. Nonlinear and delayed impacts of climate on dengue risk in Barbados: A modelling study. PLOS Med. 2018;15:e1002613.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMordecai EA, Cohen JM, Evans MV, Gudapati P, Johnson LR, Lippi CA, et al. Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models. PLoS Negl Trop Dis. 2017;11:e0005568.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuber DG, Gulledge J. Extreme Weather and Climate Change: Understanding the Link, Managing the Risk. White Pap Sci Impacts Program. 2011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. WHO | Global Strategy for dengue prevention and control, 2012\u0026ndash;2020. 2012. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/denguecontrol/9789241504034/en/\u003c/span\u003e\u003cspan address=\"https://www.who.int/denguecontrol/9789241504034/en/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 27 Oct 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLabeaud AD, Bashir F, King CH. Measuring the burden of arboviral diseases: the spectrum of morbidity and mortality from four prevalent infections. Popul Health Metr. 2011;9:1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva MMO, Tauro LB, Kikuti M, Anjos RO, Santos VC, Gon\u0026ccedil;alves TSF, et al. Concomitant Transmission of Dengue, Chikungunya, and Zika Viruses in Brazil: Clinical and Epidemiological Findings From Surveillance for Acute Febrile Illness. Clin Infect Dis. 2019;69:1353\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWard C, Chapman J. Chikungunya in Children: A Clinical Review. Pediatr Emerg Care. 2018;34:510\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrossi-Soyster EN, LaBeaud AD. Clinical aspects of Zika virus. Curr Opin Pediatr. 2017;29:102\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePuntasecca CJ, King CH, LaBeaud AD. Measuring the global burden of chikungunya and Zika viruses: A systematic review. PLoS Negl Trop Dis. 2021;15:e0009055.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrystosik A, Njoroge G, Odhiambo L, Forsyth JE, Mutuku F, LaBeaud AD. Solid Wastes Provide Breeding Sites, Burrows, and Food for Biological Disease Vectors, and Urban Zoonotic Reservoirs: A Call to Action for Solutions-Based Research. Front Public Health. 2020;7:405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGetachew D, Tekie H, Gebre-Michael T, Balkew M, Mesfin A. Breeding Sites of \u003cem\u003eAedes aegypti\u003c/em\u003e: Potential Dengue Vectors in Dire Dawa, East Ethiopia. Interdiscip Perspect Infect Dis. 2015;2015:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan A, Bisanzio D, Mutuku F, Ndenga B, Grossi-Soyster EN, Jembe Z, et al. Spatiotemporal overlapping of dengue, chikungunya, and malaria infections in children in Kenya. BMC Infect Dis. 2023;23:183.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNosrat C, Altamirano J, Anyamba A, Caldwell JM, Damoah R, Mutuku F, et al. Impact of recent climate extremes on mosquito-borne disease transmission in Kenya. PLoS Negl Trop Dis. 2021;15:e0009182.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForsyth JE, Kempinsky A, Pitchik HO, Alberts CJ, Mutuku FM, Kibe L, et al. Larval source reduction with a purpose: Designing and evaluating a household- and school-based intervention in coastal Kenya. PLoS Negl Trop Dis. 2022;16:e0010199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMwakutwaa AS, Ngugi HN, Ndenga BA, Krystosik A, Ngari M, Abubakar LU, et al. Pupal productivity of larval habitats of Aedes aegypti in Msambweni, Kwale County, Kenya. Parasitol Res. 2023;122:801\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForsyth JE, Mutuku FM, Kibe L, Mwashee L, Bongo J, Egemba C, et al. Source reduction with a purpose: Mosquito ecology and community perspectives offer insights for improving household mosquito management in coastal Kenya. PLoS Negl Trop Dis. 2020;14:e0008239.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNgugi HN, Mutuku FM, Ndenga BA, Musunzaji PS, Mbakaya JO, Aswani P, et al. Characterization and productivity profiles of Aedes aegypti (L.) breeding habitats across rural and urban landscapes in western and coastal Kenya. Parasit Vectors. 2017;10:331.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNgugi HN, Nyathi S, Krystosik A, Ndenga B, Mbakaya JO, Aswani P, et al. Risk factors for Aedes aegypti household pupal persistence in longitudinal entomological household surveys in urban and rural Kenya. Parasit Vectors. 2020;13:499.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSekhon DH, Minhas DS. A study of larval indices of Aedes and the risk for Dengue outbreak. Sch Acad J Biosci. 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHayes JM, Garc\u0026iacute;a-Rivera E, Flores-Reyna R, Su\u0026aacute;rez-Rangel G, Biggerstaff BJ, Rodr\u0026iacute;guez-Mata T, et al. Risk factors for infection during a severe dengue outbreak in El Salvador in 2000. Am J Trop Med Hyg. 2003;69:629\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGustave J, Fouque F, Cassadou S, Leon L, Anicet G, Ramdini C, et al. Increasing Role of Roof Gutters as Aedes aegypti (Diptera: Culicidae) Breeding Sites in Guadeloupe (French West Indies) and Consequences on Dengue Transmission and Vector Control. J Trop Med. 2012;2012:249524.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrewin BJ, Darbro JM, Zalucki MP, Jansen CC, Schellhorn NA, Devine GJ. Life on the margin: Rainwater tanks facilitate overwintering of the dengue vector, Aedes aegypti, in a sub-tropical climate. PLoS ONE. 2019;14:e0211167.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSukiato F, Wasserman RJ, Foo SC, Wilson RF, Cuthbert RN. The effects of temperature and shading on mortality and development rates of Aedes aegypti (Diptera: Culicidae). J Vector Ecol J Soc Vector Ecol. 2019;44:264\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLippi CA, Stewart-Ibarra AM, Endy TP, Abbott M, Cueva C, Heras F, et al. Exploring the utility of social-ecological and entomological risk factors for dengue infection as surveillance indicators in the dengue hyper-endemic city of Machala, Ecuador. PLoS Negl Trop Dis. 2021;15:e0009257.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKohn M. Occurrence of Aedes aegypti (L.) and Culex quinquefasciatus Say (Diptera, Culicidae) in houses of different constructions in Phnom Penh, Kampuchea. Folia Parasitol (Praha). 1991;38:75\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManrique-Saide P, Herrera-Boj\u0026oacute;rquez J, Villegas-Chim J, Puerta-Guardo H, Ayora-Talavera G, Parra-Carde\u0026ntilde;a M, et al. Protective effect of house screening against indoor Aedes aegypti in M\u0026eacute;rida, Mexico: A cluster randomised controlled trial. Trop Med Int Health TM IH. 2021;26:1677\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaker JL, Gadgil GU. East Asia and Pacific Cities: Expanding Opportunities for the Urban Poor. Washington, DC: World Bank; 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMavian C, Dulcey M, Munoz O, Salemi M, Vittor AY, Capua I. Islands as Hotspots for Emerging Mosquito-Borne Viruses: A One-Health Perspective. Viruses. 2018;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrayitno A, Taurel A-F, Nealon J, Satari HI, Karyanti MR, Sekartini R, et al. Dengue seroprevalence and force of primary infection in a representative population of urban dwelling Indonesian children. PLoS Negl Trop Dis. 2017;11:e0005621.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMordecai EA, Caldwell JM, Grossman MK, Lippi CA, Johnson LR, Neira M, et al. Thermal biology of mosquito-borne disease. Ecol Lett. 2019;22:1690\u0026ndash;708.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHii YL, Zhu H, Ng N, Ng LC, Rockl\u0026ouml;v J. Forecast of Dengue Incidence Using Temperature and Rainfall. PLoS Negl Trop Dis. 2012;6:e1908.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaldwell JM, LaBeaud AD, Lambin EF, Stewart-Ibarra AM, Ndenga BA, Mutuku FM, et al. Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents. Nat Commun. 2021;12:1233.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodysill JR, Russell JM, Vuille M, Dee S, Lunghino B, Bijaksana S. La Ni\u0026ntilde;a-driven flooding in the Indo-Pacific warm pool during the past millennium. Quat Sci Rev. 2019;225:106020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUmmenhofer CC, D\u0026rsquo;Arrigo RD, Anchukaitis KJ, Buckley BM, Cook ER. Links between Indo-Pacific climate variability and drought in the Monsoon Asia Drought Atlas. Clim Dyn. 2013;40:1319\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStatistics Indonesia. Statistical Yearbook of Indonesia 2014. Statistics Indonesia; 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeder K, Openshaw JJ, Allotey P, Ansariadi A, Barker SF, Burge K, et al. Study design, rationale and methods of the Revitalising Informal Settlements and their Environments (RISE) study: a cluster randomised controlled trial to evaluate environmental and human health impacts of a water-sensitive intervention in informal settlements in Indonesia and Fiji. BMJ Open. 2021;11:e042850.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitaker HJ, Farrington CP. Estimation of infectious disease parameters from serological survey data: the impact of regular epidemics. Stat Med. 2004;23:2429\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTedijanto C, Solomon AW, Martin DL, Nash SD, Keenan JD, Lietman TM, et al. Monitoring transmission intensity of trachoma with serology. Nat Commun. 2023;14:3269.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSasmono RT, Taurel A-F, Prayitno A, Sitompul H, Yohan B, Hayati RF, et al. Dengue virus serotype distribution based on serological evidence in pediatric urban population in Indonesia. PLoS Negl Trop Dis. 2018;12:e0006616.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSasmono RT, Johar E, Yohan B, Ma\u0026rsquo;roef CN, Pronyk P, Hadinegoro SR, et al. Spatiotemporal Heterogeneity of Zika Virus Transmission in Indonesia: Serosurveillance Data from a Pediatric Population. Am J Trop Med Hyg. 2021;104:2220\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKucharski AJ, Kama M, Watson CH, Aubry M, Funk S, Henderson AD et al. Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji. eLife. 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatthews RJ, Kaluthotage I, Russell TL, Knox TB, Horwood PF, Craig AT. Arboviral Disease Outbreaks in the Pacific Islands Countries and Areas, 2014 to 2020: A Systematic Literature and Document Review. Pathogens. 2022;11:74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoore TC, Brown HE. Estimating Aedes aegypti (Diptera: Culicidae) Flight Distance: Meta-Data Analysis. J Med Entomol. 2022;59:1164\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanerjee S, Aditya G, Saha GK. Household disposables as breeding habitats of dengue vectors: Linking wastes and public health. Waste Manag. 2013;33:233\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanerjee S, Aditya G, Saha GK. Household Wastes as Larval Habitats of Dengue Vectors: Comparison between Urban and Rural Areas of Kolkata, India. PLoS ONE. 2015;10:e0138082.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDieng H, Satho T, Meli NKKB, Abang F, Nolasco-Hipolito C, Hakim H, et al. Occurrence of sweet refuse at disposal sites: rainwater retention capacity and potential breeding opportunities for Aedes aegypti. Environ Sci Pollut Res Int. 2018;25:13833\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaikh OA, Baig MT, Tahir S, Parekh A-DE, Nashwan AJ. Dengue outbreak following unprecedented flooding in Pakistan. Hyg Environ Health Adv. 2023;7:100076.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNICEF Peru Flash Update No. 1 (Flooding and Dengue Outbreak) \u0026ndash;\u0026thinsp;01 Dec 2023\u0026ndash;01 March 2024 - Peru | ReliefWeb. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://reliefweb.int/report/peru/unicef-peru-flash-update-no-1-flooding-and-dengue-outbreak-01-dec-2023-01-march-2024\u003c/span\u003e\u003cspan address=\"https://reliefweb.int/report/peru/unicef-peru-flash-update-no-1-flooding-and-dengue-outbreak-01-dec-2023-01-march-2024\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 16 Jul 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePost-Flood Dengue Outbreak Puts UAE Migrant Workers at Heightened Risk. \u0026ndash; FairSquare. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://fairsq.org/post-flood-dengue-outbreak-puts-uae-migrant-workers-at-heightened-risk/\u003c/span\u003e\u003cspan address=\"https://fairsq.org/post-flood-dengue-outbreak-puts-uae-migrant-workers-at-heightened-risk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 16 Jul 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoalson JE, Anderson EJ, Santos EM, Madera Garcia V, Romine JK, Dominguez B, et al. The Complex Epidemiological Relationship between Flooding Events and Human Outbreaks of Mosquito-Borne Diseases: A Scoping Review. Environ Health Perspect. 2021;129:96002.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Aedes, trash, waste, arboviruses, vector borne diseases, dengue, built environment","lastPublishedDoi":"10.21203/rs.3.rs-5141509/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5141509/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe burden of \u003cem\u003eAedes aegypti\u003c/em\u003e-transmitted viruses such as dengue, chikungunya, and Zika are increasing globally, fueled by urbanization and climate change, with some of the highest current rates of transmission in Asia. Local factors in the built environment have the potential to exacerbate or mitigate transmission.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn 24 informal urban settlements in Makassar, Indonesia and Suva, Fiji, we tested children under 5 years old for evidence of prior infection with dengue, chikungunya, and Zika viruses by IgG serology. We used a catalytic model using seroprevalence and mean age to estimate annual incidence of dengue in each country. We also conducted detailed questionnaires to evaluate environmental risk factors for a positive serology result. Dengue risk factors were evaluated for individual children by univariate and multivariable logistic regression accounting for settlement as a fixed effect. Trash and flooding were additionally evaluated as dengue risk factors at the settlement level by univariate linear regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn Fiji and Indonesia respectively, 46% and 33% of children under 5 years old were seropositive for dengue, 3% and 3% for chikungunya, and 9% and 2% for Zika. In Indonesia, children living in a household where trash is routinely collected and removed were significantly less likely to be dengue seropositive in both unadjusted and adjusted models [adjusted model: OR 0.3 (95% CI: 0.1\u0026ndash;0.8)]. In Indonesia, settlements with a higher proportion of households reporting flooding also had lower dengue rates (slope\u0026thinsp;=\u0026thinsp;0.44; p-value: \u0026lt;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHousehold trash collection and community flood management are important targets for interventions to mitigate the increasing risk of \u003cem\u003eAedes aegypti\u003c/em\u003e-transmitted viruses.\u003c/p\u003e","manuscriptTitle":"Seroprevalence, incidence estimates, and environmental risk factors for dengue, chikungunya, and Zika infection amongst children living in informal urban settlements in Indonesia and Fiji","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-13 06:33:14","doi":"10.21203/rs.3.rs-5141509/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-26T06:39:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-25T07:01:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-25T07:00:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2024-09-24T03:43:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d8d5e28-064a-4162-bb2d-627d3ac2329f","owner":[],"postedDate":"November 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-20T16:07:26+00:00","versionOfRecord":{"articleIdentity":"rs-5141509","link":"https://doi.org/10.1186/s12879-024-10315-1","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-01-13 15:57:58","publishedOnDateReadable":"January 13th, 2025"},"versionCreatedAt":"2024-11-13 06:33:14","video":"","vorDoi":"10.1186/s12879-024-10315-1","vorDoiUrl":"https://doi.org/10.1186/s12879-024-10315-1","workflowStages":[]},"version":"v1","identity":"rs-5141509","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5141509","identity":"rs-5141509","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}