Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012

Space-time scanning statistics in the prediction and evaluation of dengue epidemic clusters

Objectives

To detect clusters of dengue hemorrhagic fever in an urbanized district of Hai Phong City, Vietnam using Poisson space-time retrospective and prospective analysis.

Methods

A cross-sectional and retrospective study analyzed dengue surveillance data in the period from January 01, 2018, to December 31, 2022. Spatial-temporal scanning statistics were performed using the free software SatScan v10.1.2.

Results

A total of 519 cases were recorded. The cumulative incidence per 100,000 inhabitants was 3.37, 127.36, 10.96, 0, and 296.04 in 2018, 2019, 2020, 2021, and 2022, respectively. By retrospective Poisson model-based analysis, seven clusters were detected. Six of these seven detected outbreaks occurred in November and December 2022. The largest cluster had a relative risk (RR) of 1539.5 (P <0.00001). The smallest cluster has a RR of 316.1 (P = 0.006). Prospective analysis using the Poisson model significantly detected four active case clusters at the time of the study. The largest cluster of cases with RR was 47.7 (P <0.00001) and the smallest cluster with RR was 18.2 (P <0.00001).

Conclusions

This study provides a basis for improving the effectiveness of interventions and conducting further investigations into risk factors in the study area, as well as in other urban and suburban areas nationwide.

The Impact of Sociological and Environmental Factors for Dengue Infection in Kuala Lumpur, Malaysia

BACKGROUND

Dengue incidence has grown dramatically around the world in recent years. Vector control is the only method to reduce dengue incidence due to the lack of a vaccine available. By understanding the factors contributed to the vector densities such as environmental and sociological factors, dengue prevention and control may succeed.

OBJECTIVE

This study is aimed at determining the impact of sociological and environmental factors contributing to dengue cases.

METHODS

The study surveyed 379 respondents with dengue history. The socio-environmental factors were evaluated by chi-square and binary regression.

RESULT

The chi-square results revealed sociological factors associated between family with dengue experience such as older age (p =0.012), fewer than four people in the household (p= 0.008), working people (p= 0.004) and apartment/terrace houses (p=0.023). Similarly, there is a significant association between respondent's dengue history and houses that are shaded with vegetation (p= 0.012) and the present of public playground areas near the residential (p = 0.011).

CONCLUSION

The study identified socio-environmental factors that play an important role in the abundance of Aedes mosquitoes and also for the local dengue control measures.

Spatial and temporal patterns of dengue incidence in Bhutan: a Bayesian analysis

Dengue is an important emerging vector-borne disease in Bhutan. This study aimed to quantify the spatial and temporal patterns of dengue and their relationship to environmental factors in dengue-affected areas at the sub-district level. A multivariate zero-inflated Poisson regression model was developed using a Bayesian framework with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure. The posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. A total of 708 dengue cases were notified through national surveillance between January 2016 and June 2019. Individuals aged ≤14 years were found to be 53% (95% CrI: 42%, 62%) less likely to have dengue infection than those aged >14 years. Dengue cases increased by 63% (95% CrI: 49%, 77%) for a 1°C increase in maximum temperature, and decreased by 48% (95% CrI: 25%, 64%) for a one-unit increase in normalized difference vegetation index (NDVI). There was significant residual spatial clustering after accounting for climate and environmental variables. The temporal trend was significantly higher than the national average in eastern sub-districts. The findings highlight the impact of climate and environmental variables on dengue transmission and suggests prioritizing high-risk areas for control strategies.

Australian Aedes aegypti mosquitoes are susceptible to infection with a highly divergent and sylvatic strain of dengue virus type 2 but are unlikely to transmit it

Background

Humans are the primary hosts of dengue viruses (DENV). However, sylvatic cycles of transmission can occur among non-human primates and human encroachment into forested regions can be a source of emergence of new strains such as the highly divergent and sylvatic strain of DENV2, QML22, recovered from a dengue fever patient returning to Australia from Borneo. The objective of the present study was to evaluate the vector competence of Australian Aedes aegypti mosquitoes for this virus.

Methods

Four- to five-day-old mosquitoes from two strains of Ae. aegypti from Queensland, Australia, were fed a meal of sheep blood containing 10⁸ 50% cell culture infectious dose per ml (CCID₅₀/ml) of either QML22 or an epidemic strain of DENV serotype 2 (QML16) isolated from a dengue fever patient in Australia in 2015. Mosquitoes were maintained at 28 °C, 75% relative humidity and sampled 7, 10 and 14 days post-infection (dpi). Live virions in mosquito bodies (abdomen/thorax), legs and wings and saliva expectorates from individual mosquitoes were quantified using a cell culture enzyme-linked immunosorbent assay (CCELISA) to determine infection, dissemination and transmission rates.

Results

The infection and dissemination rates of the sylvatic DENV2 strain, QML22, were significantly lower than that for QML16. While the titres of virus in the bodies of mosquitoes infected with either of these viruses were similar, titres in legs and wings were significantly lower in mosquitoes infected with QML22 at most time points although they reached similar levels by 14 dpi. QML16 was detected in 16% (n = 25) and 28% (n = 25) of saliva expectorates at 10 and 14 dpi, respectively. In contrast, no virus was detected in the saliva expectorates of QML22 infected mosquitoes.

Conclusions

Australia urban/peri-urban Ae. aegypti species are susceptible to infection by the sylvatic and highly divergent DENV 2 QML22 but replication of QML22 is attenuated relative to the contemporary strain, QML16. A salivary gland infection or escape barrier may be acting to prevent infection of saliva and would prevent onward transmission of this highly divergent virus in Australia.

Spatiotemporal analysis of insecticide-treated net use for children under 5 in relation to socioeconomic gradients in Central and East Africa

BACKGROUND

Insecticide-treated net (ITN) use is the core intervention among the strategies against malaria in sub-Saharan Africa (SSA) and the percentage of ITN ownership has increased from 47% in 2010 to 72% in 2017 across countries in SSA. Regardless of this massive expansion of ITN distribution, considerable gap between ownership and use of ITNs has been reported. Using data from more than 100,000 households in Central and East Africa (CEA) countries, the main aim of this study was to identify barriers associated with low ITN use and conduct geospatial analyses to estimate numbers and locations of vulnerable children living in areas with high malaria and low ITN use.

METHODS

Main sources of data for this study were the Demographic and Health Surveys and Malaria Indicator Surveys conducted in 11 countries in CEA. Logistic regression models for each country were built to assess the association between ITN ownership or ITN use and several socioeconomic and demographic variables. A density map of children under 5 living in areas at high-risk of malaria and low ITN use was generated to estimate the number of children who are living in these high malaria burden areas.

RESULTS

Results obtained suggest that factors such as the number of members in the household, total number of children in the household, education and place of residence can be key factors linked to the use of ITN for protecting children against malaria in CEA. Results from the spatiotemporal analyses found that although total rates of ownership and use of ITNs across CEA have increased up to 70% and 48%, respectively, a large proportion of children under 5 (19,780,678; 23% of total number of children) still lives in high-risk malaria areas with low use of ITNs.

CONCLUSION

The results indicate that despite substantial progress in the distribution of ITNs in CEA, with about 70% of the households having an ITN, several socioeconomic factors have compromised the effectiveness of this control intervention against malaria, and only about 48% of the households protect their children under 5 with ITNs. Increasing the effective ITN use by targeting these factors and the areas where vulnerable children reside can be a core strategy meant to reducing malaria transmission.

Spatial and temporal analysis of dengue infections in Queensland, Australia: Recent trend and perspectives

Dengue is a public health concern in northern Queensland, Australia. This study aimed to explore spatial and temporal characteristics of dengue cases in Queensland, and to identify high-risk areas after a 2009 dengue outbreak at fine spatial scale and thereby help in planning resource allocation for dengue control measures. Notifications of dengue cases for Queensland at Statistical Local Area (SLA) level were obtained from Queensland Health for the period 2010 to 2015. Spatial and temporal analysis was performed, including plotting of seasonal distribution and decomposition of cases, using regression models and creating choropleth maps of cumulative incidence. Both the space-time scan statistic (SaTScan) and Geographical Information System (GIS) were used to identify and visualise the space-time clusters of dengue cases at SLA level. A total of 1,773 dengue cases with 632 (35.65%) autochthonous cases and 1,141 (64.35%) overseas acquired cases were satisfied for the analysis in Queensland during the study period. Both autochthonous and overseas acquired cases occurred more frequently in autumn and showed a geographically expanding trend over the study period. The most likely cluster of autochthonous cases (Relative Risk, RR = 54.52, p<0.001) contained 50 SLAs in the north-east region of the state around Cairns occurred during 2013-2015. A cluster of overseas cases (RR of 60.81, p<0.001) occurred in a suburb of Brisbane during 2012 to 2013. These results show a clear spatiotemporal trend of recent dengue cases in Queensland, providing evidence in directing future investigations on risk factors of this disease and effective interventions in the high-risk areas.

Forest cover and climate as potential drivers for dengue fever in Sumatra and Kalimantan 2006-2016: a spatiotemporal analysis

OBJECTIVES

To describe and quantify spatiotemporal trends of dengue fever at district level in Sumatra and Kalimantan, Indonesia in relation to forest cover and climatic factors.

METHODS

A spatial ecological study design was used to analyse monthly surveillance data of notified dengue fever cases from January 2006 to December 2016 in the 154 districts of Sumatra and 56 districts of Kalimantan. A multivariate, zero-inflated Poisson regression model was developed with a conditional autoregressive prior structure with posterior parameters estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs sampling.

RESULTS

There were 230 745 cases in Sumatra and 132 186 cases in Kalimantan during the study period. In Sumatra, the risk of dengue fever decreased by 9% (95% credible interval [CrI] 8.5-9.5%) for a 1% increase in forest cover and by 12.2% (95% CrI 11.9-12.6%) for a 1% increase in relative humidity. In Kalimantan, dengue fever risk fell by 17.6% (95% CrI 17.1-18.1%) for a 1% increase in relative humidity and rose by 7.6% (95% CrI 6.9-8.4%) for a 1 °C increase in minimum temperature. There was no significant residual spatial clustering in Sumatra after accounting for climate and demographic variables. In Kalimantan, high residual risk areas were primarily centred in North and East of the island.

CONCLUSIONS

Dengue fever in Sumatra and Kalimantan was highly seasonal and associated with climate factors and deforestation. Incorporation of climate indicators into risk-based surveillance might be warranted for dengue fever in Indonesia.

Sociodemographic, climatic variability and lower respiratory tract infections: a systematic literature review

Pneumonia is the leading cause of mortality and morbidity in developing countries, particularly for children and elderly. The main objective of this review paper is to review the epidemiological evidence about the effects of sociodemographic and climatic variability on pneumonia and other lower respiratory tract infections. A detailed literature search was conducted in PubMed and Scopus following PRISMA guidelines. The articles, which considered the effect of only climatic or both climatic and sociodemographic factors on pneumonia and other lower respiratory tract infections, included in this review. A total thirty-four relevant articles were reviewed. Of 34 studies, only 14 articles (41%) examined the joint effects of sociodemographic and climate factors on pneumonia and other lower respiratory infections while most of them (59%) assessed climate factors separately. Among these fourteen, only three articles (8.8%) considered detailed sociodemographic factors. All of the reviewed articles suggested different degrees of positive or negative relationship of temperature with pneumonia or other lower respiratory tract infections. Fifteen (44%) articles suggested an association with relative humidity and 13 (38%) with rainfall. Only 3 articles (8.8%) found a relationship with wind speed. Three articles (8.8%) considered other risk factors such as particulate matter 2.5 (PM_2.5) and particulate matter 10 (PM₁₀). One study among the reviewed articles used spatial analysis methods but this study did not examine the joint effects. Among the reviewed articles, 18 (53%) articles used different time series models, one article (3%) used spatiotemporal time series model, 8 (23%) studies used other models and rest 7 (21%) studies used simple descriptive analysis. A total of 18 studies (53%) were conducted in Asia, most of them in China. There were 6 studies (17%) in Europe and 8 studies (23%) in America (South, North and Central). In Africa and Oceania, only one study was found for each region. The joint effect of climate and sociodemographic factors on pneumonia and other lower respiratory tract infections remain to be determined and further research is highly recommended for future prevention of this important and common disease.

Capturing the spatial variability of HIV epidemics in South Africa and Tanzania using routine healthcare facility data

BACKGROUND

Large geographical variations in the intensity of the HIV epidemic in sub-Saharan Africa call for geographically targeted resource allocation where burdens are greatest. However, data available for mapping the geographic variability of HIV prevalence and detecting HIV 'hotspots' is scarce, and population-based surveillance data are not always available. Here, we evaluated the viability of using clinic-based HIV prevalence data to measure the spatial variability of HIV in South Africa and Tanzania.

METHODS

Population-based and clinic-based HIV data from a small HIV hyper-endemic rural community in South Africa as well as for the country of Tanzania were used to map smoothed HIV prevalence using kernel interpolation techniques. Spatial variables were included in clinic-based models using co-kriging methods to assess whether cofactors improve clinic-based spatial HIV prevalence predictions. Clinic- and population-based smoothed prevalence maps were compared using partial rank correlation coefficients and residual local indicators of spatial autocorrelation.

RESULTS

Routinely-collected clinic-based data captured most of the geographical heterogeneity described by population-based data but failed to detect some pockets of high prevalence. Analyses indicated that clinic-based data could accurately predict the spatial location of so-called HIV 'hotspots' in > 50% of the high HIV burden areas.

CONCLUSION

Clinic-based data can be used to accurately map the broad spatial structure of HIV prevalence and to identify most of the areas where the burden of the infection is concentrated (HIV 'hotspots'). Where population-based data are not available, HIV data collected from health facilities may provide a second-best option to generate valid spatial prevalence estimates for geographical targeting and resource allocation.

Climate variability and dengue hemorrhagic fever in Southeast Sulawesi Province, Indonesia

To determine the association of climatic factors and dengue hemorrhagic fever and to develop the prediction approach of future dengue transmission. The study used totally monthly dengue hemorrhagic fever cases at Health Office Kendari, Southeast Sulawesi, Indonesia. Monthly meteorological data, consisting of temperature, rainfall, and humidity, was obtained from the Meteorology, Climatology and Geophysics Agency in Kendari district. All data analysis, including Spearman and Poisson distribution, was carried out in R Studio (version 3.3.2) utilizing the R statistical language version 2.15. The highest rate of dengue hemorrhagic fever cases was found in January, February, and March. Temperature averages at lag 2 (p = 0.53, p < 0.0001), lag 3 (p = 0.59, p < 0.0001), and lag 4 (p = 0.41, p < 0.01)) correlated with the incident rate of DHF. The average temperature at lag 2 was found to have a positive impact on the incidence of DHF by Poisson function. This study provides preliminary evidence of the influence of climatic factors on dengue transmission.

DETERMINATION OF ENVIRONMENTAL FACTORS AFFECTING DENGUE INCIDENCE IN SLEMAN DISTRICT, YOGYAKARTA, INDONESIA

Background:

Dengue is a disease related to the environment that spreads rapidly. Prevention movement is considered ineffective; therefore, a more efficient early warning system is required. It is required strongly correlated variables to as predictor in early warning system. This study aims to identify the environmental conditions associated with dengue.

Materials and methods:

This ecological study was conducted on five sub-districts selected based on the trend of the incidence. Data land cover and elevation obtained using GIS. Climate data were obtained from Meteorology and Climatology and Geophysics Agency of Yogyakarta.

Results:

There were 1.150 dengue cases from 2008-2013 obtained from District Health Office. The spatial pattern is clustered in all sub-districts (Z-score < -2.58). There is a positive correlation between land cover and dengue (p 0.000; r 0.284) and a negative correlation between elevation areas and dengue (p 0.000; r - 0.127). Multiple Regression Test shows the effect of humidity (p 0.000) and rainfall (p 0.002) with a contribution of 13.5% - 27.4% (r² 0.135 – 0.274), while temperature has no effect in all sub-districts (p > 0.05). There is no effect of climate parameters in sporadic dengue areas (p > 0.05).

Conclusion:

It is concluded that dengue in Sleman is clustered and associated with the environment parameter, even though it does not have close correlation. High elevated and small building area is consistent with the lower dengue cases. Humidity and rainfall affect dengue, but temperature does not affect dengue.

The spatial and temporal scales of local dengue virus transmission in natural settings: a retrospective analysis

Background

Dengue is a vector-borne disease caused by the dengue virus (DENV). Despite the crucial role of Aedes mosquitoes in DENV transmission, pure vector indices poorly correlate with human infections. Therefore there is great need for a better understanding of the spatial and temporal scales of DENV transmission between mosquitoes and humans. Here, we have systematically monitored the circulation of DENV in individual Aedes spp. mosquitoes and human patients from Caratinga, a dengue endemic city in the state of Minas Gerais, in Southeast Brazil. From these data, we have developed a novel stochastic point process pattern algorithm to identify the spatial and temporal association between DENV infected mosquitoes and human patients.

Methods

The algorithm comprises of: (i) parameterization of the variogram for the incidence of each DENV serotype in mosquitoes; (ii) identification of the spatial and temporal ranges and variances of DENV incidence in mosquitoes in the proximity of humans infected with dengue; and (iii) analysis of the association between a set of environmental variables and DENV incidence in mosquitoes in the proximity of humans infected with dengue using a spatio-temporal additive, geostatistical linear model.

Results

DENV serotypes 1 and 3 were the most common virus serotypes detected in both mosquitoes and humans. Using the data on each virus serotype separately, our spatio-temporal analyses indicated that infected humans were located in areas with the highest DENV incidence in mosquitoes, when incidence is calculated within 2.5–3 km and 50 days (credible interval 30–70 days) before onset of symptoms in humans. These measurements are in agreement with expected distances covered by mosquitoes and humans and the time for virus incubation. Finally, DENV incidence in mosquitoes found in the vicinity of infected humans correlated well with the low wind speed, higher air temperature and northerly winds that were more likely to favor vector survival and dispersal in Caratinga.

Conclusions

We have proposed a new way of modeling bivariate point pattern on the transmission of arthropod-borne pathogens between vector and host when the location of infection in the latter is known. This strategy avoids some of the strong and unrealistic assumptions made by other point-process models. Regarding virus transmission in Caratinga, our model showed a strong and significant association between high DENV incidence in mosquitoes and the onset of symptoms in humans at specific spatial and temporal windows. Together, our results indicate that vector surveillance must be a priority for dengue control. Nevertheless, localized vector control at distances lower than 2.5 km around premises with infected vectors in densely populated areas are not likely to be effective.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2662-6) contains supplementary material, which is available to authorized users.

Spatial and temporal patterns of dengue infections in Timor-Leste, 2005-2013

Background

Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease.

Methods

Notifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling.

Results

The analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ≥ 14 years were found to be 74% [95% credible interval (CrI): 72–76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4–21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6–0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29–59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables.

Conclusions

Dengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection.

Electronic supplementary material

The online version of this article (10.1186/s13071-017-2588-4) contains supplementary material, which is available to authorized users.

Endemic Australian arboviruses of human health significance

Each year many thousands of cases of human arbovirus infection are notified within Australia, acquired either within Australia or when travelling overseas1. These cause diseases varying from fever and aches, to debilitating joint disease, to encephalitis and death. The arboviruses endemic to Australia are all maintained in a cycle between mosquitoes (and rarely midges) and a bird or mammalian host2. As such, the virus activity is dependent on rainfall and temperature conditions that are conducive to mosquito breeding, and to virus replication and amplification (Figure 1). Those conditions being met, there have to be suitable amplifying animal hosts nearby, and their absence is one of the factors that protects most of the larger urban populations in Australia. Then, of course, humans have to be exposed to the infected mosquitoes to get disease.

Mapping the spatial variability of HIV infection in Sub-Saharan Africa: Effective information for localized HIV prevention and control

Under the premise that in a resource-constrained environment such as Sub-Saharan Africa it is not possible to do everything, to everyone, everywhere, detailed geographical knowledge about the HIV epidemic becomes essential to tailor programmatic responses to specific local needs. However, the design and evaluation of national HIV programs often rely on aggregated national level data. Against this background, here we proposed a model to produce high-resolution maps of intranational estimates of HIV prevalence in Kenya, Malawi, Mozambique and Tanzania based on spatial variables. The HIV prevalence maps generated highlight the stark spatial disparities in the epidemic within a country, and localize areas where both the burden and drivers of the HIV epidemic are concentrated. Under an era focused on optimal allocation of evidence-based interventions for populations at greatest risk in areas of greatest HIV burden, as proposed by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United States President's Emergency Plan for AIDS Relief (PEPFAR), such maps provide essential information that strategically targets geographic areas and populations where resources can achieve the greatest impact.

Assessing the risk of dengue virus transmission in a non-endemic city surrounded by endemic and hyperendemic areas

OBJECTIVE

To assess the potential risk of dengue transmission in a non-endemic city using a spatial epidemiological approach.

METHODS

Past dengue exposure of the general population was examined by dengue virus (DENV) IgG testing of archived samples from voluntary blood donors. Vector intensities were determined by local ovitrap index (OI). Analyses were made in the context of population statistics at both the district and sub-district level.

RESULTS

The overall prevalence of DENV IgG was low at 2.25%. Positive donors were more likely to be older, non-Chinese, and female. Neither the OI nor the location of residence was associated with DENV serology. The sub-district level OI was clustered, but no correlation could be confirmed with the location of residence of positive blood donors.

CONCLUSIONS

The cumulative exposure of Hong Kong residents to dengue has so far been low. Coupled with the lack of a spatial relationship between exposed cases and vector intensities, a high risk of local transmission of DENV is not supported. The apparently higher exposure likelihood of females could be explained by past infection in workers from dengue endemic countries, while frequent travel could have exposed older adults to DENV. Continued surveillance, risk assessment, and intensive vector control remain essential to prevent the transformation of a non-endemic to an endemic city.

The inevitable colonisation of Singapore by Zika virus

Singapore is endemic for Dengue virus, with approximately 10,000 to 20,000 annual cases reported in recent years. In 2012, Chikungunya was introduced, although the numbers of cases reported is much fewer. The current Zika virus pandemic originating in Brazil represents a threat to all regions with Aedes mosquitoes, particularly those well connected by travellers. In this respect, it was felt inevitable that Singapore would eventually realise its third endemic flavivirus. In late August 2016, a primary care practitioner observed a cluster of geographically linked patients attending with fever and rash. This resulted in the first identification of locally transmitted Zika in Singapore on August 27, 2016. This prompted a robust response in an attempt to stop further spread, which continued for approximately 10 days until a large number of laboratory-confirmed cases were found as a result of active case finding. Surprisingly, the strain was later identified to be of Asian lineage and distinct from that originating in the Americas, prompting speculation over the epidemiology of this under recognised virus in Asia.

Epidemiological risk factors for adult dengue in Singapore: an 8-year nested test negative case control study

Background

Understanding changes in the ecology and epidemiology of dengue is important to ensure resource intensive control programmes are targeted effectively as well as to inform future dengue vaccination strategies.

Methods

We analyzed data from a multicentre longitudinal prospective study of fever in adults using a nested test negative case control approach to identify epidemiological risk factors for dengue disease in Singapore. From April 2005 to February 2013, adult patients presenting with fever within 72 h at selected public primary healthcare clinics and a tertiary hospital in Singapore were recruited. Acute and convalescent blood samples were collected and used to diagnose dengue using both PCR and serology methods. A dengue case was defined as having a positive RT-PCR result for DENV OR evidence of serological conversion between acute and convalescent blood samples. Similarly, controls were chosen from patients in the cohort who tested negative for dengue using the same laboratory methods.

Results

The host epidemiological factors which increased the likelihood of dengue disease amongst adults in Singapore were those aged between 21 and 40 years old (2 fold increase) while in contrast, Malay ethnicity was protective (OR 0.57, 95%CI 0.35 to 0.91) against dengue disease. Spatial factors which increased the odds of acquiring dengue was residing at a foreign workers dormitory or hostel (OR 3.25, 95 % CI 1.84 to 5.73) while individuals living in the North-West region of the country were less likely to get dengue (OR 0.50, 95%CI 0.29 to 0.86). Other factors such as gender, whether one primarily works indoors or outdoors, general dwelling type or floor, the type of transportation one uses to work, travel history, as well as self-reported history of mosquito bite or household dengue/fever were not useful in helping to inform a diagnosis of dengue.

Conclusions

We have demonstrated a test negative study design to better understand the epidemiological risk factors of adult dengue over multiple seasons. We were able to discount other previously speculated factors such as gender, whether one primarily works indoors or outdoors, dwelling floor in a building and the use of public transportation as having no effect on one’s risk of getting dengue.

Dengue and chikungunya: modelling the expansion of mosquito-borne viruses into naïve populations

With the recent global spread of a number of mosquito-borne viruses, there is an urgent need to understand the factors that contribute to the ability of viruses to expand into naïve populations. Using dengue and chikungunya viruses as case studies, we detail the necessary components of the expansion process: presence of the mosquito vector; introduction of the virus; and suitable conditions for local transmission. For each component we review the existing modelling approaches that have been used to understand recent emergence events or to assess the risk of future expansions. We identify gaps in our knowledge that are related to each of the distinct aspects of the human-mosquito transmission cycle: mosquito ecology; human-mosquito contact; mosquito-virus interactions; and human-virus interactions. Bridging these gaps poses challenges to both modellers and empiricists, but only through further integration of models and data will we improve our ability to better understand, and ultimately control, several infectious diseases that exert a significant burden on human health.

Epidemiology of dengue fever in Hanoi from 2002 to 2010 and its meteorological determinants

Background

Dengue fever (DF) is a growing public health problem in Vietnam. The disease burden in Vietnam has been increasing for decades. In Hanoi, in contrast to many other regions, extrinsic drivers such as weather have not been proved to be predictive of disease frequency, which limits the usefulness of such factors in an early warning system.

Aims

The purpose of this research was to review the epidemiology of DF transmission and investigate the role of weather factors contributing to occurrence of DF cases.

Methods

Monthly data from Hanoi (2002–2010) were used to test the proposed model. Descriptive time-series analysis was conducted. Stepwise multivariate linear regression analysis assuming a negative binomial distribution was established through several models. The predictors used were lags of 1–3 months previous observations of mean rainfall, mean temperature, DF cases, and their interactions.

Results

Descriptive analysis showed that DF occurred annually and seasonally with an increasing time trend in Hanoi. The annual low occurred from December to March followed by a gradual increase from April to July with a peak in September, October. The amplitude of the annual peak varied between years. Statistically significant relationships were estimated at lag 1–3 with rainfall, autocorrelation, and their interaction while temperature was estimated as influential at lag 3 only. For these relationships, the final model determined a correlation of 92% between predicted number of dengue cases and the observed dengue disease frequencies.

Conclusions

Although the model performance was good, the findings suggest that other forces related to urbanization, density of population, globalization with increasing transport of people and goods, herd immunity, government vector control capacity, and changes in serotypes are also likely influencing the transmission of DF. Additional research taking into account all of these factors besides climatic factors is needed to help developing and developed countries find the right intervention for controlling DF epidemics, and to set up early warning systems with high sensitivity and specificity. Immediate action to control DF outbreak in Hanoi should include an information, communication, and education program that focuses on training Hanoi residents to more efficiently eliminate stagnant puddles and water containers after each rainfall to limit the vector population growth.

Spatiotemporal transmission dynamics of hemorrhagic fever with renal syndrome in China, 2005-2012

Background

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem with 90% of the total reported cases in the world. This study describes the spatiotemporal dynamics of HFRS cases in China and identifies the regions, time, and populations at highest risk, which could help the planning and implementation of key preventative measures.

Methods

Data on all reported HFRS cases at the county level from January 2005 to December 2012 were collected from Chinese Center for Disease Control and Prevention. Geographic Information System-based spatiotemporal analyses including Local Indicators of Spatial Association and Kulldorff's space-time scan statistic were performed to detect local high-risk space-time clusters of HFRS in China. In addition, cases from high-risk and low-risk counties were compared to identify significant demographic differences.

Results

A total of 100,868 cases were reported during 2005–2012 in mainland China. There were significant variations in the spatiotemporal dynamics of HFRS. HFRS cases occurred most frequently in June, November, and December. There was a significant positive spatial autocorrelation of HFRS incidence during the study periods, with Moran's I values ranging from 0.46 to 0.56 (P<0.05). Several distinct HFRS cluster areas were identified, mainly concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties.

Conclusions

This study identified significant space-time clusters of HFRS in China during 2005–2012 indicating that preventative strategies for HFRS should be particularly focused on the northeastern, central, and eastern of China to achieve the most cost-effective outcomes.

Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne viral disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem and accounts for 90% of the reported cases in the world. We examined the spatiotemporal dynamics of HFRS cases in China during 2005–2012 and compared characteristics between cases from high-risk and low-risk counties. Several distinct HFRS cluster areas were identified, concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties. These findings suggest preventative strategies for HFRS should be focused on the identified clusters in order to achieve the most cost-effective outcomes.

Epidemiology of dengue in a high-income country: a case study in Queensland, Australia

Background

Australia is one of the few high-income countries where dengue transmission regularly occurs. Dengue is a major health threat in North Queensland (NQ), where the vector Aedes aegypti is present. Whether NQ should be considered as a dengue endemic or epidemic region is an ongoing debate. To help address this issue, we analysed the characteristics of locally-acquired (LA) and imported dengue cases in NQ through time and space. We describe the epidemiology of dengue in NQ from 1995 to 2011, to identify areas to target interventions. We also investigated the timeliness of notification and identified high-risk areas.

Methods

Data sets of notified cases and viraemic arrivals from overseas were analysed. We developed a time series based on the LA cases and performed an analysis to capture the relationship between incidence rate and demographic factors. Spatial analysis was used to visualise incidence rates through space and time.

Results

Between 1995 and 2011, 93.9% of reported dengue cases were LA, mainly in the ‘Cairns and Hinterland’ district; 49.7% were males, and the mean age was 38.0 years old. The sources of imported cases (6.1%) were Indonesia (24.6%), Papua New Guinea (23.2%), Thailand (13.4%), East Timor (8.9%) and the Philippines (6.7%), consistent with national data. Travellers importing dengue were predominantly in the age groups 30–34 and 45–49 years old, whereas the age range of patients who acquired dengue locally was larger. The number of LA cases correlated with the number of viraemic importations. Duration of viraemia of public health importance was positively correlated with the delay in notification. Dengue incidence varied over the year and was typically highest in summer and autumn. However, dengue activity has been reported in winter, and a number of outbreaks resulted in transmission year-round.

Conclusions

This study emphasizes the importance of delay in notification and consequent duration of viraemia of public health importance for dengue outbreak duration. It also highlights the need for targeted vector control programmes and surveillance of travellers at airports as well as regularly affected local areas. Given the likely increase in dengue transmission with climate change, endemicity in NQ may become a very real possibility.

Electronic supplementary material

The online version of this article (doi:10.1186/1756-3305-7-379) contains supplementary material, which is available to authorized users.