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.

Background: Time series analysis is suitable forinvestigations of relatively direct and short-term effects of exposures on outcomes.In environmental epidemiology studies, this method has been one of the standardapproaches to assess impacts of environmental factors on acute non-infectious diseases(e.g. cardiovascular deaths), with conventionally generalized linear or additivemodels (GLM and GAM). However, the same manner of practices of this method is observedwith infectious diseases despite of the substantial differences fromnon-infectious diseases which may result in analytical challenges. Methods: Following Preferred ReportingItems for Systematic Reviews and Meta-Analyses guideline, systematic review wasconducted to elucidate important issues in assessing the associations betweenenvironmental factors and infectious diseases using time series analysis withGLM or GAM. Published studies in relation to associations between weatherfactors, and malaria, cholera, dengue, or influenza were targeted. Findings: Issues regarding theestimation of susceptible population and exposure lag times, adequacy ofseasonal adjustments, the presence of strong autocorrelations, and a lack of smallerobservation time unit of outcomes (i.e. daily data) were raised from our review.These concerns may be attributed to the features specific to infectious diseases,such as transmissions among individuals and complicated causal mechanisms. Conclusion: The consequence of not takingadequate measures to address these issues is distortion of the appropriate riskquantifications of exposures factors. The future studies are required careful attentionsto details, and recommended to examine alternative models or methods thatimprove studies with time series regression analysis for environmental determinantsof infectious diseases.

Rotavirus is a leading cause of severe acute gastroenteritis in children worldwide, and globally licensed vaccines are available. To expedite the introduction of rotavirus vaccines in the national immunisation programme, a simple, ecological method to monitor changes in the burden of rotavirus disease may be of great help. Here, we report an application of a time-series analysis on a publicly-available dataset in Japan on the weekly number of laboratory-confirmed rotavirus-positive samples over the last 5 year period between the 36th week of 2009 and the 35th week of 2014 during which rotavirus vaccines became marketed in Japan and presumed to reach an uptake rate of at least 39% as a national average. Compared with the expected number of rotavirus detection based on the preceding four rotavirus seasons, the number of rotavirus detection during the 2013–2014 season was 42.9% (95% CI: 38.6, 47.8). This suggests that the use of rotavirus vaccine had a positive impact on reducing the burden of rotavirus diarrhoea in Japan. This method, because of its simplicity and little cost, should be applicable to early detection of the impact of rotavirus vaccine even in resource-poor countries where the World Health Organization funded and implemented the sentinel surveillance programmes of laboratory-confirmed rotavirus cases.

Rotavirus is a leading cause of severe acutegastroenteritis in children worldwide, and globally licensed vaccines areavailable. To expedite the introduction of rotavirus vaccines in the nationalimmunisation programme, a simple, economical method to monitor changes in theburden of rotavirus disease may be of great help. Here, we report anapplication of a time-seriesanalysis on a publicly-available dataset in Japan on the weekly number oflaboratory-confirmed rotavirus-positive samples over the last 5 year period betweenthe 36th week of 2009 and the 35th week of 2014 during which rotavirus vaccines became marketed in Japan andpresumed to reach an uptake rate of at least 39% as a national average. Comparedwith the expected number of rotavirus detection based on the preceding four rotavirusseasons, the number of rotavirus detection during the 2013-2014 season was 43%(95% CI: 38.6, 47.8). This suggeststhat the use of rotavirus vaccine had a positive impact on reducing the burdenof rotavirus diarrhoea in Japan. This method, because of its simplicity andlittle cost, should be applicable to early detection of the impact of rotavirusvaccine even in resource-poor countries where the World Health Organizationfunded and implemented the sentinel surveillance programmes oflaboratory-confirmed rotavirus cases.

Anemia is a severe public health problem in the Lao People’s Democratic Republic (PDR). Consequently, a new control strategy to reduce the burden of anemia has been introduced for preschool children (aged 6–52 months). The objective of this study was to assess the current prevalence of anemia and related factors in preschool children in southern rural Lao PDR. A population-based cross-sectional study was carried out in six communities in Songkhone district, Savannakheth province, in February 2009. As a result, the prevalence of anemia was found to be 48.9% (95% confidence interval (CI), 43.5–54.3), although most cases were mild. A multiple logistic regression analysis indicated that there was no protective effect of breastfeeding against anemia. The anemia prevalence was higher in 1) children aged 6–23 months (Odds Ratio (OR) = 1.73, 95% CI, 1.02–2.90) than in older children, 2) children in large families (6 or more members) (OR = 1.96, 95% CI, 1.17–3.29), and 3) children in three remote villages with relatively difficult access to markets (OR = 3.01, 95% CI, 1.25–7.47).
In Lao PDR, improvement of food practices and home-fortified food supplementation interventions are essential. High-risk groups should be targeted and a long-term health education program that aims to modify food habits implemented. Furthermore, in settings where iron deficiency is not the only cause of anemia, combining an iron supplement with other measures is necessary.

Background: The health impacts of climate change are an issue of growing concern in the Pacific region. Prior to 2010, no formal, structured, evidence-based approach had been used to identify the most significant health risks posed by climate change in Pacific island countries. During 2010 and 2011, the World Health Organization supported the Federated States of Micronesia (FSM) in performing a climate change and health vulnerability and adaptation assessment. This paper summarizes the priority climate-sensitive health risks in FSM, with a focus on diarrheal disease, its link with climatic variables and the implications of climate change. Methods: The vulnerability and adaptation assessment process included a review of the literature, extensive stakeholder consultations, ranking of climate-sensitive health risks, and analysis of the available long-term data on climate and climate-sensitive infectious diseases in FSM, which involved examination of health information data from the four state hospitals in FSM between 2000 and 2010; along with each state’s rainfall, temperature and El Niño-Southern Oscillation data. Generalized linear Poisson regression models were used to demonstrate associations between monthly climate variables and cases of climate-sensitive diseases at differing temporal lags. Results: Infectious diseases were among the highest priority climate-sensitive health risks identified in FSM, particularly diarrheal diseases, vector-borne diseases and leptospirosis. Correlation with climate data demonstrated significant associations between monthly maximum temperature and monthly outpatient cases of diarrheal disease in Pohnpei and Kosrae at a lag of one month and 0 to 3 months, respectively; no such associations were observed in Chuuk or Yap. Significant correlations between disease incidence and El Niño-Southern Oscillation cycles were demonstrated in Kosrae state. Conclusions: Analysis of the available data demonstrated significant associations between climate variables and climate-sensitive infectious diseases. This information should prove useful in implementing health system and community adaptation strategies to avoid the most serious impacts of climate change on health in FSM.

Background: The health impacts of climate change are an issue of growing concern in the Pacific region.  Prior to 2010, no formal, structured, evidence-based approach had been used to identify the most significant health risks posed by climate change in Pacific island countries.  During 2010 and 2011, the World Health Organization supported the Federated States of Micronesia (FSM) in performing a climate change and health vulnerability and adaptation assessment.  This paper summarizes the priority climate-sensitive health risks in FSM, with a focus on diarrhoeal disease, its link with climatic variables and the implications of climate change. Methods:  The vulnerability and adaptation assessment process included a review of the literature, extensive stakeholder consultations, ranking of climate-sensitive health risks, and analysis of the available long-term data on climate and climate-sensitive infectious diseases in FSM, which involved examination of health information data from the four state hospitals in FSM between 2000 and 2010; along with each state’s rainfall, temperature and El Niño-Southern Oscillation data.  Generalized linear Poisson regression models were used to demonstrate associations between monthly climate variables and cases of climate-sensitive diseases at differing temporal lags. Results: Infectious diseases were among the highest priority climate-sensitive health risks identified in FSM, particularly diarrheal diseases, vector-borne diseases and leptospirosis.  Correlation with climate data demonstrated significant associations between monthly maximum temperature and monthly outpatient cases of diarrheal disease in Pohnpei and Kosrae at a lag of one month and 0 to 3 months, respectively; no such associations were observed in Chuuk or Yap.  Significant correlations between disease incidence and El Niño-Southern Oscillation cycles were demonstrated in Kosrae state. Conclusions:  Analysis of the available data demonstrated some significant associations between climate variables and climate-sensitive infectious diseases.   This information should prove useful in implementing health system and community adaptation strategies to avoid the most serious impacts of climate change on health in FSM.

Introduction: No formal curriculum has been formulated for teaching behavioral science to undergraduate medical students in Japan.
Method: We conducted a survey using the Delphi method to investigate the required competency in behavioral science for graduates in medicine. Then, we developed an outcome-oriented curriculum for teaching behavioral science.
Results: We propose an educational module of behavioral science consisting of 15 sessions of 90-minute lectures, small group discussions, and practice.
Discussion: We recommend including not only lectures but also practices according to problem-based learning as well as team-based learning in the curriculum to achieve the target outcome.