A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases

Background: Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g.cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Findings: Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. Conclusion: The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases

Comparison of contact patterns relevant for transmission of respiratory pathogens in Thailand and the Netherlands using respondent-driven sampling

Understanding infection dynamics of respiratory diseases requires the identification and quantification of behavioural, social and environmental factors that permit the transmission of these infections between humans. Little empirical information is available about contact patterns within real-world social networks, let alone on differences in these contact networks between populations that differ considerably on a socio-cultural level. Here we compared contact network data that were collected in the Netherlands and Thailand using a similar online respondent-driven method. By asking participants to recruit contact persons we studied network links relevant for the transmission of respiratory infections. We studied correlations between recruiter and recruited contacts to investigate mixing patterns in the observed social network components. In both countries, mixing patterns were assortative by demographic variables and random by total numbers of contacts. However, in Thailand participants reported overall more contacts which resulted in higher effective contact rates. Our findings provide new insights on numbers of contacts and mixing patterns in two different populations. These data could be used to improve parameterisation of mathematical models used to design control strategies. Although the spread of infections through populations depends on more factors, found similarities suggest that spread may be similar in the Netherlands and Thailand

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects

Population Dynamics of Aedes aegypti and Dengue as Influenced by Weather and Human Behavior in San Juan, Puerto Rico

Previous studies on the influence of weather on Aedes aegypti dynamics in Puerto Rico suggested that rainfall was a significant driver of immature mosquito populations and dengue incidence, but mostly in the drier areas of the island. We conducted a longitudinal study of Ae. aegypti in two neighborhoods of the metropolitan area of San Juan city, Puerto Rico where rainfall is more uniformly distributed throughout the year. We assessed the impacts of rainfall, temperature, and human activities on the temporal dynamics of adult Ae. aegypti and oviposition. Changes in adult mosquitoes were monitored with BG-Sentinel traps and oviposition activity with CDC enhanced ovitraps. Pupal surveys were conducted during the drier and wetter parts of the year in both neighborhoods to determine the contribution of humans and rains to mosquito production. Mosquito dynamics in each neighborhood was compared with dengue incidence in their respective municipalities during the study. Our results showed that: 1. Most pupae were produced in containers managed by people, which explains the prevalence of adult mosquitoes at times when rainfall was scant; 2. Water meters were documented for the first time as productive habitats for Ae. aegypti; 3. Even though Puerto Rico has a reliable supply of tap water and an active tire recycling program, water storage containers and discarded tires were important mosquito producers; 4. Peaks in mosquito density preceded maximum dengue incidence; and 5. Ae. aegypti dynamics were driven by weather and human activity and oviposition was significantly correlated with dengue incidence

Effects of the El Niño-Southern Oscillation on dengue epidemics in Thailand, 1996-2005

<p>Abstract</p> <p>Background</p> <p>Despite intensive vector control efforts, dengue epidemics continue to occur throughout Southeast Asia in multi-annual cycles. Weather is considered an important factor in these cycles, but the extent to which the El Niño-Southern Oscillation (ENSO) is a driving force behind dengue epidemics remains unclear.</p> <p>Methods</p> <p>We examined the temporal relationship between El Niño and the occurrence of dengue epidemics, and constructed Poisson autoregressive models for incidences of dengue cases. Global ENSO records, dengue surveillance data, and local meteorological data in two geographically diverse regions in Thailand (the tropical southern coastal region and the northern inland mountainous region) were analyzed.</p> <p>Results</p> <p>The strength of El Niño was consistently a predictor for the occurrence of dengue epidemics throughout time lags from 1 to 11 months in the two selected regions of Thailand. Up to 22% (in 8 northern inland mountainous provinces) and 15% (in 5 southern tropical coastal provinces) of the variation in the monthly incidence of dengue cases were attributable to global ENSO cycles. Province-level predictive models were fitted using 1996-2004 data and validated with out-of-fit data from 2005. The multivariate ENSO index was an independent predictor in 10 of the 13 studied provinces.</p> <p>Conclusion</p> <p>El Niño is one of the important driving forces for dengue epidemics across the geographically diverse regions of Thailand; however, spatial heterogeneity in the effect exists. The effects of El Niño should be taken into account in future epidemic forecasting for public health preparedness.</p

The Role of Imported Cases and Favorable Meteorological Conditions in the Onset of Dengue Epidemics

Dengue/dengue hemorrhagic fever is the world's most widely spread mosquito-borne arboviral disease and threatens more than two-thirds of the world's population. Cases are mainly distributed in tropical and subtropical areas in accordance with vector habitats for Aedes aegypti and Ae. albopictus. However, the role of imported cases and favorable meteorological conditions has not yet been quantitatively assessed. This study verified the correlation between the occurrence of indigenous dengue and imported cases in the context of weather variables (temperature, rainfall, relative humidity, etc.) for different time lags in southern Taiwan. Our findings imply that imported cases have a role in igniting indigenous outbreaks, in non-endemics areas, when favorable weather conditions are present. This relationship becomes insignificant in the late phase of local dengue epidemics. Therefore, early detection and case management of imported cases through timely surveillance and rapid laboratory-diagnosis may avert large scale epidemics of dengue/dengue hemorrhagic fever. An early-warning surveillance system integrating meteorological data will be an invaluable tool for successful prevention and control of dengue, particularly in non-endemic countries

Quantifying the Emergence of Dengue in Hanoi, Vietnam: 1998–2009

Dengue is the most common vector-borne viral disease of humans, causing an estimated 50 million cases per year. The number of countries affected by dengue has increased dramatically in the last 50 years and dengue is now a major public health problem in large parts of the tropical and subtropical world. It is of considerable importance to understand the factors that determine how dengue becomes newly established in areas where the risk of dengue was previously small. Hanoi in North Vietnam is a large city where dengue appears to be emerging. We analyzed 12 years of dengue surveillance data in order to characterize the temporal and spatial epidemiology of dengue in Hanoi and to establish if dengue incidence has been increasing. After excluding the two major outbreak years of 1998 and 2009 and correcting for changes in population age structure over time, we found there was a significant annual increase in the incidence of notified dengue cases over the period 1999–2008. Dengue cases were concentrated in young adults in the highly urban central areas of Hanoi. This study indicates that dengue transmission is increasing in Hanoi and provides a platform for further studies of the underlying drivers of this emergence

Effective contact rates <i>C</i>.

<p>Effective contact rates <i>C</i>.</p