Time-series Poisson Regression Research Articles

The influence of weather on mortality in rural Tanzania: a time-series analysis 1999–2010

Background: Weather and climate changes are associated with a number of immediate and long-term impacts on human health that occur directly or indirectly, through mediating variables. Few studies to date have established the empirical relationship between monthly weather and mortality in sub-Saharan Africa.Objectives: The objectives of this study were to assess the association between monthly weather (temperature and rainfall) on all-cause mortality by age in Rufiji, Tanzania, and to determine the differential susceptibility by age groups.Methods: We used mortality data from Rufiji Health and Demographic Surveillance System (RHDSS) for the period 1999 to 2010. Time-series Poisson regression models were used to estimate the association between monthly weather and mortality adjusted for long-term trends. We used a distributed lag model to estimate the delayed association of monthly weather on mortality. We stratified the analyses per age group to assess susceptibility.Results: In general, rainfall was found to have a stronger association in the age group 0–4 years (RR=1.001, 95% CI=0.961–1.041) in both short and long lag times, with an overall increase of 1.4% in mortality risk for a 10 mm rise in rainfall. On the other hand, monthly average temperature had a stronger association with death in all ages while mortality increased with falling monthly temperature. The association per age group was estimated as: age group 0–4 (RR=0.934, 95% CI=0.894–0.974), age group 5–59 (RR=0.956, 95% CI=0.928–0.985) and age group over 60 (RR=0.946, 95% CI=0.912–0.979). The age group 5–59 experienced more delayed lag associations. This suggests that children and older adults are most sensitive to weather related mortality.Conclusion: These results suggest that an early alert system based on monthly weather information may be useful for disease control management, to reduce and prevent fatal effects related to weather and monthly weather.

Abstract 136: Impact of Massachusetts Health Reform on Racial and Ethnic Disparities in Use of Inpatient Cardiovascular Surgeries

BACKGROUND The 2006 Massachusetts (MA) health reform increased insurance coverage to near-universal levels, but its impact on access to care or disparities in access is unclear. We examined post-reform change in racial/ethnic differences in use of two cardiovascular (CV) procedures, percutaneous transluminal coronary angioplasty (PTCA) and coronary artery bypass graft (CABG), for which disparities in use have been noted in numerous past studies. As use of these procedures is sensitive to outpatient referral, impact of reform on procedure use can serve as a marker for impact on access to care. We hypothesized that reform will result in increased use of procedures, and that the increase in use will be greater among minorities. We contrasted the results with those for two comparable orthopedic procedures (total knee replacement [TKR] and total hip replacement [THR]). METHODS Using the comprehensive MA Hospital Inpatient Data of all discharges in all non-Federal hospitals from 1/1/2004 to 9/30/2009, we obtained state-level counts of individual procedures stratified into 30 cohorts by age (40-44, 45-49, 50-54, 55-59 & 60-64), sex and race/ethnicity (Whites, Blacks and Hispanics) for each quarter. To separate the impact of MA reform from secular changes, we used corresponding data from New York (SPARCS Inpatient Data) to capture changes unrelated to MA reform. To convert procedure counts into rates (# procedures/10,000 population), we obtained Census data to create a measure of population at risk for each cohort. Treating a quarter as the unit of time, the study period comprised of 10 pre-reform, 6 transition and 7 post-reform quarters. Applying a difference-in-difference specification, we used segmented time series Poisson regression models to estimate the impact of MA reform on the procedure rates for Blacks and Hispanics relative to those for Whites. RESULTS There was a secular decrease in MA in the use of PTCA and CABG (-8.0% per year for each) throughout the study period. In MA, compared to Whites, pre-reform rates of both procedures were lower among Blacks (Incidence Rate Ratio [IRR]: PTCA=0.79 & CABG=0.73; all p values < 0.001) but similar among Hispanics. For the post-reform period, the procedure rate in MA was unchanged for PTCA but was 11% higher (95%CI=[2%, 20%]) for CABG. MA reform was associated with 11% higher post-reform rates of PTCA+CABG (combined) use among Hispanics, albeit with marginal significance (95% CI=[-1%, 25%]), than that among Whites; no significant impact was noted for Blacks (2%; 95% CI=[-10%, 16%]). Orthopedic procedures experienced secular increases in use. Reform was associated with increased use of both procedures among Blacks (16%, 95% CI=[3%, 31%]) and Hispanics (42%, 95% CI=[20%, 69%]) than that among Whites. CONCLUSIONS MA health reform may have increased the use of CV and orthopedic procedures among minorities. While orthopedic procedure use increased among both Blacks and Hispanics, the increase for CV procedures was smaller in magnitude and limited to Hispanics. Impact of reform on use may vary with procedure type due to differences in pent-up demand and acuity of conditions treated.

The warning model and influence of climatic changes on hemorrhagic fever with renal syndrome in Changsha city

To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.

Nursing staff numbers and their relationship to conflict and containment rates on psychiatric wards—A cross sectional time series Poisson regression study

Background The link between positive outcomes and qualified nurse staffing levels is well established for general hospitals. Evidence on staffing levels and outcomes for mental health nursing is more sparse, contradictory and complicated by the day to day allocation of staff resources to wards with more seriously ill patients. Objective To assess whether rises in staffing numbers precede or follow levels of adverse incidents on the wards of psychiatric hospitals. Design Time series analysis of the relationship between shift to shift changes over a six month period in total conflict incidents (aggression, self-harm, absconding, drug/alcohol use, medication refusal), total containment incidents (pro re nata medication, special observation, manual restraint, show of force, time out, seclusion, coerced intramuscular medication) and nurse staffing levels. Settings 32 acute psychiatric wards in England. Methods At the end of every shift, nurses on the participating wards completed a checklist reporting the numbers of conflict and containment incidents, and the numbers of nursing staff on duty. Results Regular qualified nurse staffing levels in the preceding shifts were positively associated with raised conflict and containment levels. Conflict and containment levels in preceding shifts were not associated with nurse staffing levels. Conclusions Results support the interpretation that raised qualified nurse staffing levels lead to small increases in risks of adverse incidents, whereas adverse incidents do not lead to consequent increases in staff. These results may be explicable in terms of the power held and exerted by psychiatric nurses in relation to patients.

P2-418 Weather variability and the incidence of influenza: Bayesian time series analysis

IntroductionInfluenza is one of the most common infectious diseases in the world. Few studies have examined the quantitative relationship between weather conditions and influenza. This paper examined the potential impact...

Short Term Effects of Weather on Hand, Foot and Mouth Disease

BackgroundHand, foot, and mouth disease (HFMD) outbreaks leading to clinical and fatal complications have increased since late 1990s; especially in the Asia Pacific Region. Outbreaks of HFMD peaks in the warmer season of the year, but the underlying factors for this annual pattern and the reasons to the recent upsurge trend have not yet been established. This study analyzed the effect of short-term changes in weather on the incidence of HFMD in Singapore.MethodsThe relative risks between weekly HFMD cases and temperature and rainfall were estimated for the period 2001–2008 using time series Poisson regression models allowing for over-dispersion. Smoothing was used to allow non-linear relationship between weather and weekly HFMD cases, and to adjust for seasonality and long-term time trend. Additionally, autocorrelation was controlled and weather was allowed to have a lagged effect on HFMD incidence up to 2 weeks.ResultsWeekly temperature and rainfall showed statistically significant association with HFMD incidence at time lag of 1–2 weeks. Every 1°C increases in maximum temperature above 32°C elevated the risk of HFMD incidence by 36% (95% CI = 1.341–1.389). Simultaneously, one mm increase of weekly cumulative rainfall below 75 mm increased the risk of HFMD by 0.3% (CI = 1.002–1.003). While above 75 mm the effect was opposite and each mm increases of rainfall decreased the incidence by 0.5% (CI = 0.995–0.996). We also found that a difference between minimum and maximum temperature greater than 7°C elevated the risk of HFMD by 41% (CI = 1.388–1.439).ConclusionOur findings suggest a strong association between HFMD and weather. However, the exact reason for the association is yet to be studied. Information on maximum temperature above 32°C and moderate rainfall precede HFMD incidence could help to control and curb the up-surging trend of HFMD.

Mortality Related to Temperature and Persistent Extreme Temperatures—A Study of Cause-Specific and Age Stratified Mortality

O-29A1-2 Background/Aims: High and low ambient temperatures cause large numbers of deaths annually. Many studies show higher mortality rates during heat waves, with mortality increasing with heat wave duration. However, such effects have not been explicitly incorporated in models of temperature and mortality; while from a physiological basis, dehydration followed by cardiovascular stress is more likely to occur in such conditions. Methods: We established time-series Poisson regression models based on cause-specific mortality and age stratified mortality in Stockholm County, 1990–2002, adjusting for time trends and potential confounders. We studied the effects estimates as functions of time within summers and winters. Results: Warmer temperatures increase all natural causes of death, while decreasing colder temperatures increases the risk of cardiovascular deaths. Moreover, persistent extreme heat exposure is associated substantially with additional deaths, and the risk of death increase significantly with longer heat exposure. Extreme exposure to heat is associated with higher death rates in people with lower age, compared to a rise in temperature. Furthermore, the impact of warm and cold temperatures decreases within the season, while the impact of persistent extreme heat exposure remains similar throughout the summer. Conclusion: This study is the first to show that additional impacts of persistence of extreme heat exposure are important to account for in models of mortality related to ambient temperatures to avoid negatively biased estimates of the associated effects. Moreover, it appears that the impacts of temperature depend on the size of the pool of fragile individuals, while persistent extreme heat exposure increases the influx of new individuals to the pool and, thus, remain large throughout the season.

Mortality related to temperature and persistent extreme temperatures: a study of cause-specific and age-stratified mortality

ObjectivesHigh and low ambient temperatures are associated with large numbers of deaths annually. Many studies show higher mortalities during heatwaves. However, such effects are rarely explicitly incorporated in models of...

Climate Variability and Hemorrhagic Fever with Renal Syndrome Transmission in Northeastern China

BackgroundThe transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission.ObjectiveWe examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China.MethodsWe obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997–2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission.ResultsCross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3–5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and long-term trend, rainfall, LST, RH, and MEI with lags of 3–5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS.ConclusionsClimate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.

Excess deaths during the 2004 heatwave in Brisbane, Australia

The paper examines whether there was an excess of deaths and the relative role of temperature and ozone in a heatwave during 7-26 February 2004 in Brisbane, Australia, a subtropical city accustomed to warm weather. The data on daily counts of deaths from cardiovascular disease and non-external causes, meteorological conditions, and air pollution in Brisbane from 1 January 2001 to 31 October 2004 were supplied by the Australian Bureau of Statistics, Australian Bureau of Meteorology, and Queensland Environmental Protection Agency, respectively. The relationship between temperature and mortality was analysed using a Poisson time series regression model with smoothing splines to control for nonlinear effects of confounding factors. The highest temperature recorded in the 2004 heatwave was 42 degrees C compared with the highest recorded temperature of 34 degrees C during the same periods of 2001-2003. There was a significant relationship between exposure to heat and excess deaths in the 2004 heatwave [estimated increase in non-external deaths: 75 ([95% confidence interval, CI: 11-138; cardiovascular deaths: 41 (95% CI: -2 to 84)]. There was no apparent evidence of substantial short-term mortality displacement. The excess deaths were mainly attributed to temperature but exposure to ozone also contributed to these deaths.

The Effects of the 2004 Reduction in the Price of Alcohol on Alcohol-Related Harm in Finland – a Natural Experiment Based on Register Data

Changes in alcohol pricing have been documented as inversely associated with changes in consumption and alcohol-related problems. Evidence of the association between price changes and health problems is nevertheless patchy and is based to a large extent on cross-sectional state-level data, or time series of such cross-sectional analyses. Natural experimental studies have been called for. There was a substantial reduction in the price of alcohol in Finland in 2004 due to a reduction in alcohol taxes of one third, on average, and the abolition of duty-free allowances for travellers from the EU. These changes in the Finnish alcohol policy could be considered a natural experiment, which offered a good opportunity to study what happens with regard to alcohol-related problems when prices go down. The present study investigated the effects of this reduction in alcohol prices on (1) alcohol-related and all-cause mortality, and mortality due to cardiovascular diseases, (2) alcohol-related morbidity in terms of hospitalisation, (3) socioeconomic differentials in alcohol-related mortality, and (4) small-area differences in interpersonal violence in the Helsinki Metropolitan area. Differential trends in alcohol-related mortality prior to the price reduction were also analysed. A variety of population-based register data was used in the study. Time-series intervention analysis modelling was applied to monthly aggregations of deaths and hospitalisation for the period 1996-2006. These and other mortality analyses were carried out for men and women aged 15 years and over. Socioeconomic differentials in alcohol-related mortality were assessed on a before/after basis, mortality being followed up in 2001-2003 (before the price reduction) and 2004-2005 (after). Alcohol-related mortality was defined in all the studies on mortality on the basis of information on both underlying and contributory causes of death. Hospitalisation related to alcohol meant that there was a reference to alcohol in the primary diagnosis. Data on interpersonal violence was gathered from 86 administrative small-areas in the Helsinki Metropolitan area and was also assessed on a before/after basis followed up in 2002-2003 and 2004-2005. The statistical methods employed to analyse these data sets included time-series analysis, and Poisson and linear regression. The results of the study indicate that alcohol-related deaths increased substantially among men aged 40-69 years and among women aged 50-69 after the price reduction when trends and seasonal variation were taken into account. The increase was mainly attributable to chronic causes, particularly liver diseases. Mortality due to cardiovascular diseases and all-cause mortality, on the other hand, decreased considerably among the-over-69-year-olds. The increase in alcohol-related mortality in absolute terms among the 30-59-year-olds was largest among the unemployed and early-age pensioners, and those with a low level of education, social class or income. The relative differences in change between the education and social class subgroups were small. The employed and those under the age of 35 did not suffer from increased alcohol-related mortality in the two years following the price reduction. The gap between the age and education groups, which was substantial in the 1980s, thus further broadened. With regard to alcohol-related hospitalisation, there was an increase in both chronic and acute causes among men under the age of 70, and among women in the 50-69-year age group when trends and seasonal variation were taken into account. Alcohol dependence and other alcohol-related mental and behavioural disorders were the largest category in both the total number of chronic hospitalisation and in the increase. There was no increase in the rate of interpersonal violence in the Helsinki Metropolitan area, and even a decrease in domestic violence. There was a significant relationship between the measures of social disadvantage on the area level and interpersonal violence, although the differences in the effects of the price reduction between the different areas were small. The findings of the present study suggest that that a reduction in alcohol prices may lead to a substantial increase in alcohol-related mortality and morbidity. However, large population group differences were observed regarding responsiveness to the price changes. In particular, the less privileged, such as the unemployed, were most sensitive. In contrast, at least in the Finnish context, the younger generations and the employed do not appear to be adversely affected, and those in the older age groups may even benefit from cheaper alcohol in terms of decreased rates of CVD mortality. The results also suggest that reductions in alcohol prices do not necessarily affect interpersonal violence. The population group differences in the effects of the price changes on alcohol-related harm should be acknowledged, and therefore the policy actions should focus on the population subgroups that are primarily responsive to the price reduction.

Air quality and outpatient visits for asthma in adults during the 2008 Summer Olympic Games in Beijing

To fulfill its commitment to a successful 2008 Olympic and Paralympic Games, the Chinese government made unprecedented efforts to improve the air quality in Beijing. We report findings on air quality and outpatient visits for asthma among adults in Beijing during the 2008 Summer Olympic Games. Three study periods were defined: summer baseline (June 1–June 30: before any air pollution controls), pre-Olympics (July 1–August 7: transportation restrictions in effect), and Olympics (August 8–September 20: further restrictions on industrial emissions). Daily data on outpatient asthma visits were obtained from the asthma registry of Beijing Chaoyang Hospital. We used time-series Poisson regression models to estimate the relative risk (RR) for asthma visits associated with pollution levels. The average numbers of outpatient visit for asthma were 12.5 per day at baseline and 7.3 per day during the Olympics. Compared with baseline, the Games were associated with a significant reduction in asthma visits (RR 0.54, 95%CI: 0.39–0.75). Our analysis showed that even in a heavily-polluted city, decreased concentrations of small particles were associated with some reduction in asthma visits in adults.

Climate variability and increase in intensity and magnitude of dengue incidence in Singapore

Introduction: Dengue is currently a major public health burden in Asia Pacific Region. This study aims to establish an association between dengue incidence, mean temperature and precipitation, and further discuss how weather predictors influence the increase in intensity and magnitude of dengue in Singapore during the period 2000–2007.Materials and methods: Weekly dengue incidence data, daily mean temperature and precipitation, and the midyear population data in Singapore during 2000–2007 were retrieved and analyzed. We employed a time series Poisson regression model including time factors such as time trends, lagged terms of weather predictors, considered autocorrelation, and accounted for changes in population size by offsetting.Results: The weekly mean temperature and cumulative precipitation were statistically significant related to the increases of dengue incidence in Singapore. Our findings showed that dengue incidence increased linearly at time lag of 5–16 and 5–20 weeks succeeding elevated temperature and precipitation, respectively. However, negative association occurred at lag week 17–20 with low weekly mean temperature as well as lag week 1–4 and 17–20 with low cumulative precipitation.Discussion: As Singapore experienced higher weekly mean temperature and cumulative precipitation in the years 2004–2007, our results signified hazardous impacts of climate factors on the increase in intensity and magnitude of dengue cases. The ongoing global climate change might potentially increase the burden of dengue fever infection in near future.

The influence of meteorological factors on the emergence of preterm delivery and preterm premature rupture of membrane

To evaluate the influence of changes in the atmospheric state on the incidence of preterm delivery (PTD) and preterm premature rupture of membrane (PPROM). The hospital records of PTD and/or PPROM over the year 1999 were reviewed. The current meteorological state was described by a set of parameters and their diurnal and seasonal variations. Multivariate analysis, time series approach and Poisson regression were used. PTD occurrence was correlated with humidity and maximum temperature (P<0.01), its rise preceded their sharp variations by 3 days (P<0.01). PPROM was influenced by the variations in the weather state: desert heat wave arrival (P=0.093), strong winds, overall daily differences of humidity and temperature (all with P<0.05). The rates of PTD and PPROM are affected by an ensemble of meteorological variables, specific for each disorder. Obstetricians should be aware of the influence of unstable weather on PTD and PPROM rates, especially in the spring and autumn.

Compulsory child restraint seat law and motor vehicle child occupant deaths and injuries in Japan 1994–2005

The purpose of child restraint seats (CRS) is to reduce the number of individuals killed or injured in motor vehicle (MV) crashes. Japanese Road Traffic Law 17–3-4 (April 2000) specifies a requirement that CRS be used for all children aged 0–5 years. The objective of this evaluation was to determine the legislative impact on fatalities in Japan for the period 1994–2005. Data were obtained from the Institute for Traffic Accident Research and Data Analysis. A time-series Poisson regression model was used to analyse the change (6 years pre/post) in incidence rate ratios of fatality and injury in MV crashes among children ages 0–5 years. Despite increases in CRS use, fatalities failed to decrease significantly after enactment of the law (incidence rate ratio: 0.80; 95% CI: 0.49–1.31). In 2005, 67% of children aged 0–5 years, who were killed as MV occupants were not seated in CRS. Between 2000 and 2005, the lack of CRS led to 43% of front seat passenger deaths, 54% of rear seat deaths, 143 children died in total and 500 + children were seriously injured. It was found that the compulsory CRS law enacted in April 2000 did not result in a statistically significant reduction in child MV occupant fatalities and injuries in Japan.

Ozone modifies associations between temperature and cardiovascular mortality: analysis of the NMMAPS data

Objectives: Both ambient ozone and temperature are associated with human health. However, few data are available on whether ozone modifies temperature effects. This study aims to explore whether ozone modified...

Ozone Modifies Associations Between Temperature and Cardiovascular Mortality—The Analysis Using the NMMAPS Data

ISEE-343 Objective: Both ambient ozone and temperature are associated with human health. However, no study has examined whether ozone modifies temperature effects, although some studies have examined whether temperature modifies air pollution effects. This study was undertaken to explore whether ozone modified associations between maximum temperature and cardiovascular mortality across the United States. Material and Methods: We obtained the data from the US National Morbidity, Mortality, and Air Pollution Study (NMMAPS) Website. We used 2 time-series Poisson regression models (the response surface model and stratification model) to examine whether ozone modified associations between maximum temperature and cardiovascular mortality (CVM) in 95 large US communities during 1987 to 2000. We used Bayesian meta-analysis to pool estimates in each community. Results: The response surface model was used to examine the joint effects of temperature and ozone on CVM in summer. Results illustrate that ozone synergistically modified the temperature-CVM associations across the different regions. The stratification model quantified the temperature-CVM associations across different levels of ozone. Results show that, in general, the higher the ozone concentration, the stronger the temperature-CVM associations across the communities. A 10°C increase in temperature on the same day was associated with an increase in CVM by 1.17% and 8.31% for the lowest and highest level of ozone concentrations, respectively. Conclusions: Ozone modified temperature effects in the different regions in the United States. It is important to evaluate the modifying role of ozone while estimating temperature-related health impacts and to further investigate the reasons behind the regional variability.

Weather Variability and the Incidence of Cryptosporidiosis: Comparison of Time Series Poisson Regression and SARIMA Models

Few studies have examined the relationship between weather variables and cryptosporidiosis in Australia. This paper examines the potential impact of weather variability on the transmission of cryptosporidiosis and explores the possibility of developing an empirical forecast system. Data on weather variables, notified cryptosporidiosis cases, and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics for the period of January 1, 1996-December 31, 2004, respectively. Time series Poisson regression and seasonal auto-regression integrated moving average (SARIMA) models were performed to examine the potential impact of weather variability on the transmission of cryptosporidiosis. Both the time series Poisson regression and SARIMA models show that seasonal and monthly maximum temperature at a prior moving average of 1 and 3 months were significantly associated with cryptosporidiosis disease. It suggests that there may be 50 more cases a year for an increase of 1 degrees C maximum temperature on average in Brisbane. Model assessments indicated that the SARIMA model had better predictive ability than the Poisson regression model (SARIMA: root mean square error (RMSE): 0.40, Akaike information criterion (AIC): -12.53; Poisson regression: RMSE: 0.54, AIC: -2.84). Furthermore, the analysis of residuals shows that the time series Poisson regression appeared to violate a modeling assumption, in that residual autocorrelation persisted. The results of this study suggest that weather variability (particularly maximum temperature) may have played a significant role in the transmission of cryptosporidiosis. A SARIMA model may be a better predictive model than a Poisson regression model in the assessment of the relationship between weather variability and the incidence of cryptosporidiosis.

Correlation Between Air Pollution and Postneonatal Mortality in a Subtropical City: Taipei, Taiwan

With growing evidence of the association between daily mortality and air pollution exposure in adults, it is important to investigate whether infants are also susceptible. The purpose of this study was to examine the relationship between air pollution exposure and postneonatal, defined as infant of more than 27 d and less than 1 yr old, mortality in Taipei, Taiwan's largest city, which has a subtropical climate, for the period 1994–2000, using a case-crossover analysis. This design is an alternative to Poisson time-series regression for studying the short-term adverse health effects of air pollution. The air pollutants examined included particulate matter (PM10), sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). The risk of postneonatal deaths was estimated to increase by 3.1% for PM10, 4.1% for SO2, 1.7% for NO2, 3.8% for CO, and 0.1% for O3 for each interquartile range change, respectively. However, the associations were without statistical significance. The established link between air pollution levels and infant mortality may not be as strong in cities with subtropical climates, although other factors such as differences in pollutant component composition or the underlying health of the postneonates may explain the lack of a strong association in this study. Further studies of this type in cities with varying climates and cultures are needed.

Mosquito Species (Diptera: Culicidae) and the Transmission of Ross River Virus in Brisbane, Australia

This study aimed to identify the major mosquito vectors of Ross River virus (family Togaviridae, genus Alphavirus, RRV) and to explore the threshold of mosquito abundance necessary for RRV transmission in Brisbane, Australia. Data on the monthly counts of RRV cases by statistical local areas from the Queensland Health and the monthly mosquito abundance in Brisbane between November 1998 and December 2001 from the Brisbane City Council were used to assess the pairwise relationship between mosquito abundance and the incidence of RRV disease over a range of time lags using cross-correlations. We used time series Poisson regression models to identify major mosquito species associated with incidence of RRV after adjusting for overdispersion, maximum temperature, autocorrelation, and seasonality. Our results show that Aedes vigilax (Skuse) (relative risk [RR] = 1.32; 95% CI = 1.01-1.74 per 100 mosquitoes per trap) and Culex annulirostris (Skuse) (RR = 1.14, 95% CI = 1.04-1.24 per 100 mosquitoes per trap) were most strongly associated with RRV transmission at a lag of 1 mo. Classification and regression tree (CART) analyses indicate that the occurrence of RRV was associated with an average monthly mosquito abundance ofAedes vigilax above 72 and Cx. annulirostris above 52. The validation analyses indicate that the crude agreement between predicted values and actual observations was 76% (sensitivity, 61%; specificity, 80%). The results may have applications as a decision support tool in planning disease control and risk-management programs.