Determining meteorologically-favorable zones for seasonal influenza activity in Hong Kong.

Investigations of simple and accurate meteorology classification systems for influenza epidemics, particularly in subtropical regions, are limited. To assist in preparing for potential upsurges in the demand on healthcare facilities during influenza seasons, our study aims to develop a set of meteorologically-favorable zones for epidemics of influenza A and B, defined as the intervals of meteorological variables with prediction performance optimized. We collected weekly detection rates of laboratory-confirmed influenza cases from four local major hospitals in Hong Kong between 2004 and 2019. Meteorological and air quality records for hospitals were collected from their closest monitoring stations. We employed classification and regression trees to identify zones that optimize the prediction performance of meteorological data in influenza epidemics, defined as a weekly rate > 50th percentile over a year. According to the results, a combination of temperature > 25.1℃ and relative humidity > 79% was favorable to epidemics in hot seasons, whereas either temperature < 16.4℃ or a combination of < 20.4℃ and relative humidity > 76% was favorable to epidemics in cold seasons. The area under the receiver operating characteristic curve (AUC) in model training achieved 0.80 (95% confidence interval [CI], 0.76-0.83) and was kept at 0.71 (95%CI, 0.65-0.77) in validation. The meteorologically-favorable zones for predicting influenza A or A and B epidemics together were similar, but the AUC for predicting influenza B epidemics was comparatively lower. In conclusion, we established meteorologically-favorable zones for influenza A and B epidemics with a satisfactory prediction performance, even though the influenza seasonality in this subtropical setting was weak and type-specific.

Projecting future temperature-related mortality using annual time series data: An example from Hong Kong.

BACKGROUND: Previous studies projecting future temperature-related mortality under climate change have mostly used short-term temperature-mortality associations based on daily time series data. The present study aimed to project mortality under different Representative Concentration Pathways (RCPs) in 21st century in Hong Kong by using analysis of annual data during 1976-2018. METHODS: We employed a degree-days approach, calculating the sum of daily degrees above or below certain temperature threshold within a relevant historical year. The yearly age-standardized mortality rates (ASMRs) were regressed on annual hot and cold degree-days in quasi-Poisson generalized additive models to assess the exposure-response function that was subsequently used to calculate future changes in ASMR. The projection was performed without and with certain human adaptation assumed. RESULTS: ASMRs were projected to have net increases under RCPs 4.5, 6.0, and 8.5, with increased mortality attributable to excess hot days exceeding decreases attributable to excess cold days. The average net changes under RCP8.5 was estimated to be 0.12%, 12.44%, 38.99%, and 89.25% during 2030s, 2050s, 2070s, and 2090s, respectively. Higher projected ASMRs were estimated for those aged over 75 years and for cardiovascular deaths. When human adaptation was considered, slope reduction alone under RCP4.5 and 6.0 and all adaptation assumptions under RCP8.5 might still not offset its corresponding adverse impact. CONCLUSIONS: The projected decreases in cold-related mortality do not compensate for projected increases in heat-related mortality in Hong Kong. Better public adaptations strategies are warranted for coping with the adverse health impacts of climate change on a local scale.

Assessing spatial variability of extreme hot weather conditions in Hong Kong: A land use regression approach.

The number of extreme hot weather events have considerably increased in Hong Kong in the recent decades. The complex urban context of Hong Kong leads to a significant intra-urban spatial variability in climate. Under such circumstance, a spatial understanding of extreme hot weather condition is urgently needed for heat risk prevention and public health actions. In this study, the extreme hot weather events of Hong Kong were quantified and measured using two indicators - very hot day hours (VHDHs) and hot night hours (HNHs) which were counted based on the summertime hourly-resolved air temperature data from a total of 40 weather stations (WSs) from 2011 to 2015. Using the VHDHs and HNHs at the locations of the 40 WSs as the outcome variables, land use regression (LUR) models are developed to achieve a spatial understanding of the extreme hot weather conditions in Hong Kong. Land surface morphology was quantified as the predictor variables in LUR modelling. A total of 167 predictor variables were considered in the model development process based on a stepwise multiple linear regression (MLR). The performance of resultant LUR models was evaluated via cross validation. VHDHs and HNHs were mapped at the community level for Hong Kong. The mapping results illustrate a significant spatial variation in the extreme hot weather conditions of Hong Kong in both the daytime and nighttime, which indicates that the spatial variation of land use configurations must be considered in the risk assessment and corresponding public health management associated with the extreme hot weather.

The influence of weather on health-related help-seeking behavior of senior citizens in Hong Kong.

It is believed that extreme hot and cold weather has a negative impact on general health conditions. Much research focuses on mortality, but there is relatively little community health research. This study is aimed at identifying high-risk groups who are sensitive to extreme weather conditions, in particular, very hot and cold days, through an analysis of the health-related help-seeking patterns of over 60,000 Personal Emergency Link (PE-link) users in Hong Kong relative to weather conditions. In the study, 1,659,716 PE-link calls to the help center were analyzed. Results showed that females, older elderly, people who did not live alone, non-subsidized (relatively high-income) users, and those without medical histories of heart disease, hypertension, stroke, and diabetes were more sensitive to extreme weather condition. The results suggest that using official government weather forecast reports to predict health-related help-seeking behavior is feasible. An evidence-based strategic plan could be formulated by using a method similar to that used in this study to identify high-risk groups. Preventive measures could be established for protecting the target groups when extreme weather conditions are forecasted.

A 21-year retrospective analysis of environmental impacts on paediatric acute gastroenteritis in an affluent setting.

BACKGROUND: Extreme weather events happen more frequently along with global warming and they constitute a challenge for public health preparedness. For example, many investigations showed heavy rainfall was associated with an increased risk of acute gastroenteritis. In this study, we examined the associations between different meteorological factors and paediatric acute gastroenteritis in an affluent setting in China controlling for pollutant effects. METHODS: Aggregated total weekly number of intestinal infection-related hospital admissions, and meteorological and air pollution data during 1998-2018 in Hong Kong were collected and analysed by a combination of quasi-Poisson generalized additive model and distributed lag nonlinear model. Study population was restricted to children under 5 years of age at the time of admission. RESULTS: While heavy rainfall did not exhibit a statistically significant association with the risk of paediatric admission due to intestinal infections, low temperature and humidity extremes (both relative humidity and vapour pressure) did. Compared with the temperature at which the lowest risk was detected (i.e. 22.5 °C), the risk was 6.4% higher (95% confidence interval: 0.0% to 13.0% at 15.1 °C (i.e. the 5th percentile)). We also found the risk of paediatric admission was statistically significantly associated with an increase in the number of extreme cold days in a week over the study period. CONCLUSION: Cold condition may have greater impact on disease transmission through increased stability and infectivity of enteric viruses in affluent settings like Hong Kong and thus resulted in an increased risk for paediatric acute gastroenteritis. On the contrary, an insignificant impact from heavy rainfall and high temperature may indicate a minor effect on disease transmission through bacterial growth in contaminated food and water. With the identified impacts of weather factors, extreme weather events are likely to distort the prevalence and seasonal pattern of diarrhoeal diseases in the future.

Integrated urban services: Experience from four cities on different continents.

Rapid urbanization combined with climate change necessitates new types of urban services that make best use of science and technology. The Integrated Urban Hydro-Meteorological, Climate and Environmental Services and systems are a new initiative from the World Meteorological Organization (WMO) that seeks to provide science-based integrated urban services supporting safe, healthy and resilient cities. Various cities have already started development and implementation of such Integrated Urban Services and successfully test and use them following specific requirements of local stakeholders. This paper demonstrates the novel concept and approach of Integrated Urban Hydro-Meteorological, Climate and Environmental Services (IUS) from a set of four case study cities: Hong Kong, Toronto, Mexico City and Paris, that use different IUS configurations with good existing practice. These cities represent a range of countries, climates and geophysical settings. The aggregate main joint similarities of the IUS in these cities and synergy of the cities' experience, achievements and research findings are presented, as well as identification of existing gaps in knowledge and further research needs. A list of potential criteria for identifying and classifying IUS demonstration cities is proposed. It will aid future, more detailed analysis of the IUS experience, and selection of additional demonstration cities.

Association between meteorological variations and activities of influenza A and B across different climate zones: a multi-region modelling analysis across the globe.

OBJECTIVE: To elucidate the effects of meteorological variations on the activity of influenza A and B in 11 sites across different climate regions. METHODS: Daily numbers of laboratory-confirmed influenza A and B cases from 2011-2015 were collected from study sites where the corresponding daily mean temperature, relative humidity, wind speed and daily precipitation amount were used for boosted regression trees analysis on the marginal associations and the interaction effects. RESULTS: Cold temperature was a major determinant that favored both influenza A and B in temperate and subtropical sites. Temperature-to-influenza A, but not influenza B, exhibited a U-shape association in subtropical and tropical sites. High relative humidity was also associated with influenza activities but was less consistent with influenza B activity. Compared with relative humidity, absolute humidity had a stronger association - it was negatively associated with influenza B activity in temperate zones, but was positively associated with both influenza A and B in subtropical and tropical zones. CONCLUSION: The association between meteorological factors and with influenza activity is virus type specific and climate dependent. The heavy influence of temperature on influenza activity across climate zones implies that global warming is likely to have an impact on the influenza burden.

The impact of extremely hot weather events on all-cause mortality in a highly urbanized and densely populated subtropical city: A 10-year time-series study (2006-2015).

BACKGROUND: The impact of heatwaves on public health has led to an urgent need to describe extremely hot weather events (EHWEs) and evaluate their health impacts. METHODS: In Hong Kong, a very hot day (VHD) can be defined when the daily maximum temperature ≥ 33 °C, and a hot night (HN) can be identified if the daily minimum temperature ≥ 28 °C. Three lengths of time, nine combinations of VHD and HN, and four categories of occurrence intervals between two EHWEs were considered over 2006-2015. The daily relative risk (RR) of all-cause mortality was estimated using Poisson generalized additive regression models, controlling for both short-term and long-term trends in temperature as well as four air pollutants. Lagged effects of the representative EHWEs were further examined for their association with mortality. Subgroup analysis was conducted for different sex and age groups. RESULTS: Significant associations with raised mortality risks were observed for a single HN, while stronger associations with mortality were observed as significant for five or more consecutive VHDs/HNs. More HNs between the consecutive VHDs also significantly amplified the impact on mortality, with the strongest association observed for EHWEs characterized as 2D3N, and the effect significantly lagged for five days. Therefore, with identifiable health impacts, three thresholds (5VHDs, 5HNs, & 2D3N) were determined to be representative of identical types of EHWEs in Hong Kong. Furthermore, by taking 2 (3) consecutive VHDs (HNs) as one daytime (nighttime) EHWE event, those occurring consecutively without non-hot days (nights) in between were found to be significantly associated with excess mortality risks. Moreover, females and older adults were determined to be relatively more vulnerable to all defined EHWEs. CONCLUSIONS: Among all the observed significant heat-mortality associations in highly urbanized cities, EHWEs that occurred during the nighttime, with extended length, consecutively without any break in between, or in the pattern of 2D3N might require the meteorological administration, healthcare providers, and urban planners to work interactively.

Hospitalization Incidence, Mortality, and Seasonality of Common Respiratory Viruses Over a Period of 15 Years in a Developed Subtropical City.

Information on respiratory viruses in subtropical region is limited.Incidence, mortality, and seasonality of influenza (Flu) A/B, respiratory syncytial virus (RSV), adenovirus (ADV), and parainfluenza viruses (PIV) 1/2/3 in hospitalized patients were assessed over a 15-year period (1998-2012) in Hong Kong.Male predominance and laterally transversed J-shaped distribution in age-specific incidence was observed. Incidence of Flu A, RSV, and PIV decreased sharply from infants to toddlers; whereas Flu B and ADV increased slowly. RSV conferred higher fatality than Flu, and was the second killer among hospitalized elderly. ADV and PIV were uncommon, but had the highest fatality. RSV, PIV 2/3 admissions increased over the 15 years, whereas ADV had decreased significantly. A "high season," mainly contributed by Flu, was observed in late-winter/early-spring (February-March). The "medium season" in spring/summer (April-August) was due to Flu and RSV. The "low season" in late autumn/winter (October-December) was due to PIV and ADV. Seasonality varied between viruses, but predictable distinctive pattern for each virus existed, and temperature was the most important associating meteorological variable.Respiratory viruses exhibit strong sex- and age-predilection, and with predictable seasonality allowing strategic preparedness planning. Hospital-based surveillance is crucial for real-time assessment on severity of new variants.

Climatic influence on the prevalence of noncutaneous disease flare in systemic lupus erythematosus in Hong Kong.

OBJECTIVE: It is generally agreed that there is a seasonal variation in the prevalence of cutaneous manifestations of systemic lupus erythematosus (SLE). We investigated whether there is seasonal variation in the incidence of noncutaneous lupus flare in Hong Kong. METHODS: We reviewed all noncutaneous lupus flare in 222 consecutive patients with SLE followed in our clinic from 1995 to 2005. Specific organ involvement of each flare was reviewed. The variation in the prevalence of lupus flare by calendar month and the relation with climatic factors were determined. RESULTS: The total followup was 18,412 patient-months. In total, there were 313 episodes of noncutaneous flare recorded in 129 patients. There were more lupus flares in December and January [2.31 episodes, vs 1.58 episodes per 100 patient-months for other calendar months; relative risk (RR) 1.46, 95% CI 1.12-1.90, p = 0.004], and more flares of lupus nephritis in December and January (1.14 episodes, vs 0.60 episodes per 100 patient-months for other calendar months; RR 1.90, 95% CI 1.29-2.80, p = 0.001). There were more cases of membranous nephropathy in December and January (0.46 episode, vs 0.18 episode per 100 patient-months for other calendar months; RR 2.59, 95% CI 1.36-4.93, p = 0.0027), while the variation in prevalence of proliferative lupus nephritis was not statistically significant. There was also a significant U-shape correlation between the rate of lupus flare and the monthly average environmental temperature (r = 0.802, p = 0.0096), with higher flare rate at extremes of temperature. CONCLUSION: We found substantial seasonal variation in the incidence of noncutaneous flare in our SLE patients, with peak incidence in December and January. There was a U-shaped relation between environmental temperature and the prevalence of noncutaneous flare. Keeping a warm living environment and avoiding exposure to extremes of temperature may help to reduce flare for SLE patients in subtropical countries.