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In 1995, the Hong Kong Diabetes Register (HKDR) was established by a doctor-nurse team at a university-affiliated, publicly funded, hospital-based diabetes center using a structured protocol for gathering data to stratify risk, triage care, empower patients, and individualize treatment. This research-driven quality improvement program has motivated the introduction of a territory-wide diabetes risk assessment and management program provided by 18 hospital-based diabetes centers since 2000. By linking the data-rich HKDR to the territory-wide electronic medical record, risk equations were developed and validated to predict clinical outcomes. In 2007, the HKDR protocol was digitalized to establish the web-based Joint Asia Diabetes Evaluation (JADE) Program complete with risk levels and algorithms for issuance of personalized reports to reduce clinical inertia and empower self-management. Through this technologically assisted, integrated diabetes care program, we have generated big data to track secular trends, identify unmet needs, and verify interventions in a naturalistic environment. In 2009, the JADE Program was adapted to form the Risk Assessment and Management Program for Diabetes Mellitus (RAMP-DM) in the publicly funded primary care clinics, which reduced all major events by 30–60% in patients without complications. Meanwhile, a JADE-assisted assessment and empowerment program provided by a university-affiliated, self-funded, nurse-coordinated diabetes center, aimed at complementing medical care in the community, also reduced all major events by 30–50% in patients with different risk levels. By combining universal health coverage, public-private partnerships, and data-driven integrated care, the Hong Kong experience provides a possible solution than can be adapted elsewhere to make quality diabetes care accessible, affordable, and sustainable.

Background. Previous studies identifying associations between influenza and acute cardiac events may have been confounded by climatic factors. Differing seasonal patterns of influenza activity in Hong Kong and England and Wales provide a natural experiment to examine associations with myocardial infarction (MI) independent of cold weather effects. Methods. Weekly clinical and laboratory influenza surveillance data, environmental temperature and humidity data, and counts of MI-associated hospitalizations and deaths were obtained for England and Wales and for Hong Kong for the period 1998-2008. We used Poisson regression models that included environmental and seasonal variables to investigate the relationship between influenza and MI. Results. There were ≥ 1.2 million MI-associated hospitalizations and 410,204 MI-associated deaths in England and Wales, with a marked peak in the winter season. In Hong Kong, the incidence of MI, on the basis of 65,108 hospitalizations and 18,780 deaths, had a large winter and smaller summer peak, mirroring patterns of influenza activity. There was strong evidence for a link between influenza and MI both in England and Wales, where 3.1%-3.4% of MI-associated deaths (P < .001) and 0.7%-1.2% of MI-associated hospitalizations (P < .001) were attributable to influenza, and in Hong Kong, where the corresponding figures were 3.9%-5.6% (P = .018) and 3.0%-3.3% (P = .002). Conclusions. Influenza was associated with an increase in MI-associated deaths and hospitalizations in 2 contrasting settings. © The Author 2011. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved., link_to_OA_fulltext

Objectives To evaluate the presence of moral hazard, adjusted for the propensity to have self-purchased insurance policies, employer-based medical benefits, and welfare-associated medical benefits in Hong Kong. Methods Based on 2005 population survey, we used logistic regression and zero-truncated negative binomial/Poisson regressions to assess the presence of moral hazard by comparing inpatient and outpatient utilization between insured and uninsured individuals. We fitted each enabling factor specific to the type of service covered, and adjusted for predisposing socioeconomic and demographic factors. We used a propensity score approach to account for potential adverse selection. Results Employment-based benefits coverage was associated with increased access and intensity of use for both inpatient and outpatient care, except for public hospital use. Similarly, welfare-based coverage had comparable effect sizes as employment-based schemes, except for the total number of public ambulatory episodes. Self-purchased insurance facilitated access but did not apparently induce greater demand of services among ever users. Nevertheless, there was no evidence of moral hazard in public hospital use. Conclusions Our findings suggest that employment-based benefits coverage lead to the greatest degree of moral hazard in Hong Kong. Future studies should focus on confirming these observational findings using a randomized design.

We examined for the presence of moral hazard among those covered by medical benefits or insurance schemes, whether provided for by employers or privately purchased and stratified by health care provider sector in Hong Kong. Data for this study were derived from the 2002 Thematic Household Survey, covering 24,610 non-institutional residents aged 15 and over, representing 5,353,666 persons after applying population weights. Zero-inflated Poisson or negative binomial models were constructed to examine the association between predisposing, need and enabling factors with inpatient and outpatient utilisation patterns as per Andersen's health behavioural framework. Individuals with insurance or medical benefits were more likely to have been ever admitted in the previous year but did not incur more bed-days. Similarly, those who were covered by insurance or medical benefits had a higher probability of ever visiting a doctor in the previous month but not consuming more episodes. These findings were consistent across the public and private sectors. We propose that our observations mostly reflected realised access that met genuine health need rather than inappropriate overuse of services. A supply-driven public sector and high out-of-pocket co-payments for private services likely explained these findings.

To better understand the distribution of resources and health care consumption patterns in different geo-ethnic and socio-economic settings, we sought to describe the patterns of illness, care-seeking behavior and health services utilization in Hong Kong compared to the US and UK. Data were derived from the 2002 Hong Kong Thematic Household Survey covering 31,762 non-institutional and institutional residents, representing 6,504,255 persons after applying population weights. Of 1000 individuals during a 1-month period, 567 reported symptoms, 512 of whom considered seeking health care. Four hundred and forty persons visited western allopathic medical practitioners, with 372 (84.5%) in primary care and 68 (15.5%) in specialty care. There were 54 visits to traditional Chinese medical practitioners and 16 emergency room episodes. Seven individuals were hospitalized in community hospitals and on average one in 1000 were admitted to a tertiary medical center. Ninety out of the 567 who experienced symptoms undertook self-management strategies, which included over-the-counter western allopathic medications ( n = 54 ) or traditional Chinese remedies ( n = 14 ) or both ( n = 2 ), dietary modification ( n = 1 ) and rest ( n = 15 ). We have mapped the ecology of health care in Hong Kong. Monthly prevalence estimates were remarkably similar to US figures for hospital-based events, whereas there was evidence of apparent, substantial “over-consumption” of ambulatory, community-based care. Our results also indicate that the local community's care-seeking orientation still very much favors western allopathic medicine over traditional Chinese therapy, at least for acute illness episodes.

Seroprevalence survey is the most practical method for accurately estimating infection attack rate (IAR) in an epidemic such as influenza. These studies typically entail selecting an arbitrary titer threshold for seropositivity (e.g. microneutralization [MN] 1∶40) and assuming the probability of seropositivity given infection (infection-seropositivity probability, ISP) is 100% or similar to that among clinical cases. We hypothesize that such conventions are not necessarily robust because different thresholds may result in different IAR estimates and serologic responses of clinical cases may not be representative. To illustrate our hypothesis, we used an age-structured transmission model to fully characterize the transmission dynamics and seroprevalence rises of 2009 influenza pandemic A/H1N1 (pdmH1N1) during its first wave in Hong Kong. We estimated that while 99% of pdmH1N1 infections became MN1∶20 seropositive, only 72%, 62%, 58% and 34% of infections among age 3–12, 13–19, 20–29, 30–59 became MN1∶40 seropositive, which was much lower than the 90%–100% observed among clinical cases. The fitted model was consistent with prevailing consensus on pdmH1N1 transmission characteristics (e.g. initial reproductive number of 1.28 and mean generation time of 2.4 days which were within the consensus range), hence our ISP estimates were consistent with the transmission dynamics and temporal buildup of population-level immunity. IAR estimates in influenza seroprevalence studies are sensitive to seropositivity thresholds and ISP adjustments which in current practice are mostly chosen based on conventions instead of systematic criteria. Our results thus highlighted the need for reexamining conventional practice to develop standards for analyzing influenza serologic data (e.g. real-time assessment of bias in ISP adjustments by evaluating the consistency of IAR across multiple thresholds and with mixture models), especially in the context of pandemics when robustness and comparability of IAR estimates are most needed for informing situational awareness and risk assessment. The same principles are broadly applicable for seroprevalence studies of other infectious disease outbreaks., Author Summary Seroprevalence studies have been regarded as the most practical method for accurately estimating the number of infections in influenza epidemics and pandemics. However, methods for inferring the number of infections from seroprevalence data in previous studies have mostly been based on conventional practice instead of standardized criteria. Specifically, there are no systematic criteria on how to select the seropositivity threshold and adjust for the proportion of infections that become seropositive. Here, we showed that under the conventional criteria, the number of 2009 pandemic influenza A/H1N1 infections had been substantially underestimated in Hong Kong as well as other countries, mostly due to overestimation of the proportion of infections that became seropositive. Our results highlighted the need to reexamine the widely accepted practice in interpreting seroprevalence data, especially in the context of pandemics when little is known but robust and comparable estimates of the number of infections and severity are most needed for informing situational awareness and guiding control policies.

Open Access Journal, BACKGROUND: Obesity is closely associated with various cardiovascular diseases (CVDs). Adipose tissue inflammation and perturbation of adipokine secretion may contribute to the pathogenesis of CVD. This study aimed to evaluate whether the 2 most abundant adipokines, adipocyte-fatty acid binding protein (A-FABP) and adiponectin, are independent risk factors predisposing to CVD. METHOD AND RESULTS: We investigated prospectively the 12-year development of CVD in relation to the baseline levels of A-FABP and adiponectin in a population-based community cohort comprising 1847 Chinese subjects recruited from the Hong Kong Cardiovascular Risk Factors Prevalence Study 2 (CRISPS 2) cohort without previous CVD. Baseline serum levels of A-FABP, adiponectin, and C-reactive protein (CRP), an established biomarker predictive of CVD, were measured. In all, 182 (9.9%) of the 1847 Chinese subjects developed CVD during a median follow-up of 9.4 years. The CVD group had more traditional risk factors, higher baseline levels of A-FABP and CRP (both P, link_to_OA_fulltext

Background Cytokines released from adipose tissues induce chronic low-grade inflammation, which may enhance cancer development. We investigated whether indices of obesity and circulating adipokine levels could predict incident cancer risk. Materials and Methods This longitudinal community-based study included subjects from the Hong Kong Cardiovascular Risk Factors Prevalence Study (CRISPS) study commenced in 1995-1996 (CRISP-1) with baseline assessments including indices of obesity. Subjects were reassessed in 2000-2004 (CRISPS-2) with measurement of serum levels of adipokines including interleukin-6 (IL-6), soluble tumor necrosis factor receptor 2 (sTNFR2; as a surrogate marker of tumor necrosis factor-α activity), leptin, lipocalin 2, adiponectin and adipocyte-fatty acid binding protein (A-FABP). Incident cancer cases were identified up to 31 December 2011. Results 205 of 2893 subjects recruited at CRISPS-1 had developed incident cancers. More of the subjects who developed cancers were obese (22.1 vs 16.1%) or had central obesity (36.6 vs 24.5%) according to Asian cut-offs. Waist circumference (adjusted HR 1.02 [1.00-1.03] per cm; p=0.013), but not body mass index (adjusted HR 1.04 [1.00-1.08] per kg/m2; p=0.063), was a significant independent predictor for incident cancers after adjustment for age, sex and smoking status. 99 of 1899 subjects reassessed at CRISPS-2 had developed cancers. Subjects who developed cancers had significantly higher level of hsCRP, IL-6, sTNFR2 and lipocalin 2. After adjustment for conventional risk factors, only IL-6 (HR 1.51, 95% CI 1.18-1.95) and sTNFR2 (HR 3.27, 95%CI 1.65-6.47) predicted cancer development. Conclusions Our data supported the increased risk of malignancy by chronic low grade inflammation related to central obesity.

Background: Adipose tissue inflammation and dysregulated adipokine secretion are implicated in obesity-related insulin resistance and type 2 diabetes. We evaluated the use of serum adiponectin, an anti-inflammatory adipokine, and several proinflammatory adipokines, as biomarkers of diabetes risk and whether they add to traditional risk factors in diabetes prediction. Methods: We studied 1300 non-diabetic subjects from the prospective Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS). Serum adiponectin, tumor necrosis factor-alpha receptor 2 (TNF-α R2), interleukin-6 (IL-6), adipocyte-fatty acid binding protein (A-FABP) and high-sensitivity C-reactive protein (hsCRP) were measured in baseline samples. Results: Seventy-six participants developed diabetes over 5.3 years (median). All five biomarkers significantly improved the log-likelihood of diabetes in a clinical diabetes prediction (CDP) model including age, sex, family history of diabetes, smoking, physical activity, hypertension, waist circumference, fasting glucose and dyslipidaemia. In ROC curve analysis, "adiponectin + TNF-α R2" improved the area under ROC curve (AUC) of the CDP model from 0.802 to 0.830 (P = 0.03), rendering its performance comparable to the "CDP + 2-hour post-OGTT glucose" model (AUC = 0.852, P = 0.30). A biomarker risk score, derived from the number of biomarkers predictive of diabetes (low adiponectin, high TNF-α R2), had similar performance when added to the CDP model (AUC = 0.829 [95% CI: 0.808-0.849]). Conclusions: The combined use of serum adiponectin and TNF-α R2 as biomarkers provided added value over traditional risk factors for diabetes prediction in Chinese and could be considered as an alternative to the OGTT. © 2012 Woo et al., published_or_final_version

We studied the prevalence of self-reported diabetes mellitus in selected years from 2001 to 2008, and evaluated the factors associated with diabetes. From territory-wide household interviews in a Chinese population in the years 2001, 2002, 2005 and 2008, we evaluated the trend of self-reported diabetes with respect to age, sex and household income. Binary logistic regression analyses were conducted to study the independent factors associated with diabetes. From 121,895 respondents in the household surveys, 103,367 were adults aged 15 years or older. Among male respondents, the age- and sex-adjusted prevalence of diabetes in 2001, 2002, 2005 and 2008 was 2.80, 2.87, 3.32 and 4.66 %, respectively; while among female respondents the respective prevalence was 3.25, 3.37, 3.77 and 4.31 %. In all the years, the prevalence escalated with age and increased sharply among the poor. From binary logistic regression analyses, advanced age and low monthly household income were significantly associated with self-report of diabetes. This study showed a rising trend of diabetes mellitus in a large Chinese population and found a strong association between population demography and diabetes.

Steven Riley and colleagues analyze a community cohort study from the 2009 (H1N1) influenza pandemic in Hong Kong, and found that more children than adults were infected with H1N1, but children were less likely to progress to severe disease than adults., Background While patterns of incidence of clinical influenza have been well described, much uncertainty remains over patterns of incidence of infection. The 2009 pandemic provided both the motivation and opportunity to investigate patterns of mild and asymptomatic infection using serological techniques. However, to date, only broad epidemiological patterns have been defined, based on largely cross-sectional study designs with convenience sampling frameworks. Methods and Findings We conducted a paired serological survey of a cohort of households in Hong Kong, recruited using random digit dialing, and gathered data on severe confirmed cases from the public hospital system (>90% inpatient days). Paired sera were obtained from 770 individuals, aged 3 to 103, along with detailed individual-level and household-level risk factors for infection. Also, we extrapolated beyond the period of our study using time series of severe cases and we simulated alternate study designs using epidemiological parameters obtained from our data. Rates of infection during the period of our study decreased substantially with age: for 3–19 years, the attack rate was 39% (31%–49%); 20–39 years, 8.9% (5.3%–14.7%); 40–59 years, 5.3% (3.5%–8.0%); and 60 years or older, 0.77% (0.18%–4.2%). We estimated parameters for a parsimonious model of infection in which a linear age term and the presence of a child in the household were used to predict the log odds of infection. Patterns of symptom reporting suggested that children experienced symptoms more often than adults. The overall rate of confirmed pandemic (H1N1) 2009 influenza (H1N1pdm) deaths was 7.6 (6.2–9.5) per 100,000 infections. However, there was substantial and progressive increase in deaths per 100,000 infections with increasing age from 0.66 (0.65–0.86) for 3–19 years up to 220 (50–4,000) for 60 years and older. Extrapolating beyond the period of our study using rates of severe disease, we estimated that 56% (43%–69%) of 3–19 year olds and 16% (13%–18%) of people overall were infected by the pandemic strain up to the end of January 2010. Using simulation, we found that, during 2009, larger cohorts with shorter follow-up times could have rapidly provided similar data to those presented here. Conclusions Should H1N1pdm evolve to be more infectious in older adults, average rates of severe disease per infection could be higher in future waves: measuring such changes in severity requires studies similar to that described here. The benefit of effective vaccination against H1N1pdm infection is likely to be substantial for older individuals. Revised pandemic influenza preparedness plans should include prospective serological cohort studies. Many individuals, of all ages, remained susceptible to H1N1pdm after the main 2009 wave in Hong Kong. Please see later in the article for the Editors' Summary, Editors' Summary Background From June 2009 to August 2010, the world was officially (according to specific WHO criteria—WHO phase 6 pandemic alert) in the grip of an Influenza A pandemic with a new strain of the H1N1 virus. During this time, more than 214 countries and overseas territories reported laboratory confirmed cases of pandemic influenza H1N1 2009 with almost 20,000 deaths. While much is already known about patterns of incidence of clinical influenza, the patterns of infection incidence are much more uncertain, because many influenza infections are either asymptomatic or cause only mild symptoms. This means that it is difficult to obtain accurate estimates of risk factors for infection and the overall burden of disease using only clinical surveillance. However, without accurate estimates of infection incidence across different risk groups, it is not possible to establish the number of infections that give rise to severe disease (the per infection rate of severe disease). Consequently, it is difficult to give evidence-based advice for individuals, groups, and populations about the potential benefits of interventions including drugs and vaccines that might reduce the risk of influenza infection. Why Was This Study Done? During the 2009 pandemic, some countries and territories, such as Hong Kong, were able to investigate patterns of mild and asymptomatic infection using serological techniques, thus providing information that may help to fill this knowledge gap. Given the high levels of polymerase chain reaction (PCR) testing and the robust reporting of hospital episodes, the main H1N1 pandemic wave in Hong Kong (during September 2009) provided an opportunity to implement a prospective cohort study to investigate the incidence of infection. What Did the Researchers Do and Find? The researchers collected data on the asymptomatic symptoms of influenza by randomly selecting households to participate in the study. Each member of the household willing to participate had a baseline blood sample taken before the main wave of the pandemic (July to September 2009), then, when clinical surveillance suggested that the main peak in transmission had passed, after the main wave (November 2009 to February 2010). During the study period, participants were asked to report any flu-like symptoms in three ways: to phone the study team and report symptoms in real time; to fill out a paper diary with the day and symptoms; and to report symptoms during a follow-up interview. In parallel, the researchers monitored data on every patient with H1N1 admitted to intensive care units or who died while in the hospital. The researchers then estimated the number of H1N1 infections (infection incidence) per severe case by developing a likelihood-based framework. They used a simulation model to investigate alternate study designs and to validate their estimates of the rate of severe disease per infection. Using these methods, the researchers found that rates of H1N1 infection during the study period decreased substantially with age: for 3–19 years, the attack rate was 39%; 20–39 years, 8.9%; 40–59 years, 5.3%; and 60 years or older, 0.77%. In addition, patterns of symptom reporting indicated that children experienced symptoms more often than adults. The overall rate of confirmed H1N1 deaths was 7.6 per 100,000 infections. However, there was a substantial and progressive increase in deaths per 100,000 infections with increasing age from 0.66 for 3–19 years up to 220 for 60 years and older. Statistical modeling suggested that 56% of 3–19 year olds and 16% of people overall were infected by the pandemic strain up to the end of January 2010. What Do These Findings Mean? The results of this study suggest that more children were infected with H1N1 than adults but most of them did not progress to severe disease. Conversely, although fewer older adults were infected with H1N1, this group was much more likely to experience severe disease. Therefore, should H1N1 infection incidence ever increase in older adults, for example by evolving to become more infectious to this group, average rates of severe disease per infection could be much higher than for the 2009 pandemic. Revised pandemic preparedness plans should include prospective serological cohort studies, such as this one, in order to be able to estimate rates of severe disease per infection. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000442. WHO has information about the global response to the 2009 H1N1 pandemic WHO also provides recommendations for the H1N1 post-pandemic period The government of Hong Kong's Centre for Health Protection provides information about H1N1 in Hong Kong

This study reports that using serological data coupled with clinical surveillance data can provide real-time estimates of the infection attack rates and severity in an emerging influenza pandemic., Background In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IAR) and severity. Methods and Findings We tested 14,766 sera collected during the first wave of the 2009 pandemic in Hong Kong using viral microneutralization. We estimated IAR and infection-hospitalization probability (IHP) from the serial cross-sectional serologic data and hospitalization data. Had our serologic data been available weekly in real time, we would have obtained reliable IHP estimates 1 wk after, 1–2 wk before, and 3 wk after epidemic peak for individuals aged 5–14 y, 15–29 y, and 30–59 y. The ratio of IAR to pre-existing seroprevalence, which decreased with age, was a major determinant for the timeliness of reliable estimates. If we began sero-surveillance 3 wk after community transmission was confirmed, with 150, 350, and 500 specimens per week for individuals aged 5–14 y, 15–19 y, and 20–29 y, respectively, we would have obtained reliable IHP estimates for these age groups 4 wk before the peak. For 30–59 y olds, even 800 specimens per week would not have generated reliable estimates until the peak because the ratio of IAR to pre-existing seroprevalence for this age group was low. The performance of serial cross-sectional sero-surveillance substantially deteriorates if test specificity is not near 100% or pre-existing seroprevalence is not near zero. These potential limitations could be mitigated by choosing a higher titer cutoff for seropositivity. If the epidemic doubling time is longer than 6 d, then serial cross-sectional sero-surveillance with 300 specimens per week would yield reliable estimates when IAR reaches around 6%–10%. Conclusions Serial cross-sectional serologic data together with clinical surveillance data can allow reliable real-time estimates of IAR and severity in an emerging pandemic. Sero-surveillance for pandemics should be considered. Please see later in the article for the Editors' Summary, Editors' Summary Background Every winter, millions of people catch influenza—a viral infection of the airways—and about half a million die as a result. These seasonal epidemics occur because small but frequent changes in the influenza virus mean that the immune response produced by infection with one year's virus provides only partial protection against the next year's virus. Occasionally, however, a very different influenza virus emerges to which people have virtually no immunity. Such viruses can start global epidemics (pandemics) and kill millions of people. The most recent influenza pandemic began in March 2009 in Mexico, when the first case of influenza caused by a new virus called pandemic A/H1N1 2009 (pdmH1N1) occurred. The virus spread rapidly despite strenuous efforts by national and international public health agencies to contain it, and on 11 June 2009, the World Health Organization (WHO) declared that an influenza pandemic was underway. By the time WHO announced that the pandemic was over (10 August 2010), pdmH1N1 had killed more than 18,000 people. Why Was This Study Done? Early in the 2009 influenza pandemic, as in any emerging pandemic, reliable estimates of pdmH1N1's transmissibility (how easily it spreads between people) and severity (the proportion of infected people who needed hospital treatment) were urgently needed to help public health officials plan their response to the pandemic and advise the public about the threat to their health. Because infection with an influenza virus does not always make people ill, the only way to determine the true size and severity of an influenza outbreak is to monitor the occurrence of antibodies (proteins made by the immune system in response to infections) to the influenza virus in the population—so-called serologic surveillance. In this study, the researchers developed a method that uses serologic data to provide real-time estimates of the infection attack rate (IAR; the cumulative occurrence of new infections in a population) and the infection-hospitalization probability (IHP; the proportion of affected individuals that needs to be hospitalized) during an influenza pandemic. What Did the Researchers Do and Find? The researchers tested nearly 15,000 serum samples collected in Hong Kong during the first wave of the 2009 pandemic for antibodies to pdmH1N1 and then used a mathematical approach called convolution to estimate IAR and IHP from these serologic data and hospitalization data. They report that if the serological data had been available weekly in real time, they would have been able to obtain reliable estimates of IAR and IHP by one week after, one to two weeks before, and three weeks after the pandemic peak for 5–14 year olds, 15–29 year olds, and 30–59 year olds, respectively. If serologic surveillance had begun three weeks after confirmation of community transmission of pdmH1N1, sample sizes of 150, 350, and 500 specimens per week from 5–14 year olds, 15–19 year olds, and 20–29 year olds, respectively, would have been sufficient to obtain reliable IAR and IHP estimates four weeks before the pandemic peak. However, for 30–59 year olds, even 800 specimens per week would not have generated reliable estimates because of pre-existing antibodies to an H1N1 virus in this age group. Finally, computer simulations of future pandemics indicate that serologic surveillance with 300 serum specimens per week would yield reliable estimates of IAR and IHP as soon as the true IAR reached about 6%. What Do These Findings Mean? These findings suggest that serologic data together with clinical surveillance data could be used to provide reliable real-time estimates of IARs and severity in an emerging influenza pandemic. Although the number of samples needed to provide accurate estimates of IAR and IHP in real life may vary somewhat from those reported here because of limitations in the design of this study, these findings nevertheless suggest that the level of testing capacity needed to provide real-time estimates of IAR and IHP during an emerging influenza pandemic should be logistically feasible for most developed countries. Moreover, collection of serologic surveillance data from any major city affected early in an epidemic could potentially provide information of global relevance for public health. Thus, the researchers conclude, serologic monitoring should be included in future plans for influenza pandemic preparedness and response and in planning for other pandemics. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001103. A recent PLoS Medicine Research Article by Riley et al. provides further information on patterns of infection with the pdmH1N1 virus The Hong Kong Centre for Health Protection provides information on pandemic H1N1 influenza The US Centers for Disease Control and Prevention provides information about influenza for patients and professionals, including specific information on H1N1 influenza Flu.gov, a US government website, provides access to information on seasonal, pandemic, and H1N1 influenza WHO provides information on seasonal influenza and has information on the global response to H1N1 influenza (in several languages) The UK Health Protection Agency provides information on pandemic influenza and on H1N1 influenza More information for patients about H1N1 influenza is available through Choices, an information resource provided by the UK National Health Service

Serial cross-sectional data on antibody levels to the 2009 pandemic H1N1 influenza A virus from a population can be used to estimate the infection attack rates and immunity against future infection in the community.From April through December 2009, we obtained 12,217 serum specimens from blood donors (aged 16-59 years), 2520 specimens from hospital outpatients (aged 5-59 years), and 917 specimens from subjects involved in a community pediatric cohort study (aged 5-14 years). We estimated infection attack rates by comparing the proportions of specimens with antibody titers ≥ 1:40 by viral microneutralization before and after the first wave of the pandemic. Estimates were validated using paired serum samples from 324 individuals that spanned the first wave. Combining these estimates with epidemiologic surveillance data, we calculated the proportion of infections that led to hospitalization, admission to the intensive care unit (ICU), and death.We found that 3.3% and 14% of persons aged 5-59 years had antibody titers ≥ 1:40 before and after the first wave, respectively. The overall attack rate was 10.7%, with age stratification as follows: 43.4% in persons aged 5-14 years, 15.8% in persons aged 15-19 years, 11.8% in persons aged 20-29 years, and 4%-4.6% in persons aged 30-59 years. Case-hospitalization rates were 0.47%-0.87% among persons aged 5-59 years. Case-ICU rates were 7.9 cases per 100,000 infections in persons aged 5-14 years and 75 cases per 100,000 infections in persons aged 50-59 years, respectively. Case-fatality rates were 0.4 cases per 100,000 infections in persons aged 5-14 years and 26.5 cases per 100,000 infections in persons aged 50-59 years, respectively.Almost half of all school-aged children in Hong Kong were infected during the first wave. Compared with school children aged 5-14 years, older adults aged 50-59 years had 9.5 and 66 times higher risks of ICU admission and death if infected, respectively.

Background The main goal of Hong Kong's publicly-funded general outpatient clinics (GOPCs) is to provide primary medical services for the financially vulnerable. The objective of the current study was to compare the primary care experiences of GOPC users and the users of care provided by private general practitioners (GPs) in Hong Kong via a territory-wide telephone survey. Methods One thousand adults in Hong Kong aged 18 and above were interviewed by a telephone survey. The modified Chinese translated Primary Care Assessment Tool was used to collect data on respondents' primary care experience. Results Our results indicated that services provided by GOPC were more often used by female, older, poorer, chronically-ill and less educated population. GOPC participants were also more likely to have visited a specialist or used specialist services (69.7% vs. 52.0%; p < 0.001), although this difference in utilization of specialist services disappeared after adjusting for age (55.7% vs. 52.0%, p = 0.198). Analyses were also performed to asses the relationship between healthcare settings (GOPCs versus private GPs) and primary care quality. Private GP patients achieved higher overall PCAT scores largely due to better accessibility (Mean: 6.88 vs. 8.41, p < 0.001) and person-focused care (Mean: 8.37 vs. 11.69, p < 0.001). Conclusions Our results showed that patients primarily receiving care from private GPs in Hong Kong reported better primary care experiences than those primarily receiving care from GOPCs. This was largely due to the greater accessibility and better interpersonal relationships offered by the private GPs. As most patients use both GOPCs and private GPs, their overall primary care experiences may not be as different as the findings of this study imply.

In Hong Kong, kindergartens and primary schools were closed when local transmission of pandemic (H1N1) 2009 was identified. Secondary schools closed for summer vacation shortly afterwards. By fitting a model of reporting and transmission to case data, we estimated that transmission was reduced ≈25% when secondary schools closed., link_to_OA_fulltext

Background: Timely estimation of the transmissibility of a novel pandemic influenza virus was a public health priority in 2009. Methods: We extended methods for prospective estimation of the effective reproduction number (R t) over time in an emerging epidemic to allow for reporting delays and repeated importations. We estimated Rt based on case notifications and hospitalizations associated with laboratory-confirmed pandemic (H1N1) 2009 virus infections in Hong Kong from June through October 2009. Results: Rt declined from around 1.4-1.5 at the start of the local epidemic to around 1.1-1.2 later in the summer, suggesting changes in transmissibility perhaps related to school vacations or seasonality. Estimates of Rt based on hospitalizations of confirmed H1N1 cases closely matched estimates based on case notifications. Conclusion: Real-time monitoring of the effective reproduction number is feasible and can provide useful information to public health authorities for situational awareness and calibration of mitigation strategies. © 2010 by Lippincott Williams & Wilkins., link_to_OA_fulltext

Background An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. Methods We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. Results Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. Conclusion The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.

Background: Recognising that household interviews may produce biased estimates of health services utilisation, we examined for under- and over-reporting of hospitalisation episodes in three recent, consecutive population-based household surveys in Hong Kong. Methods: Territory-wide inpatient service utilisation volumes as estimated from the 1999, 2001 and 2002 Thematic Household Surveys (THS) were benchmarked against corresponding statistics derived from routine administrative databases. Between-year differences on net under-reporting were quantified by Cohen's d effect size. To assess the potential for systematic biases in under-reporting, age- and sex-specific net under-reporting rates within each survey year were computed and the F-test was performed to evaluate differences between demographic subgroups. We modelled the effects of age and sex on the likelihood of ever hospitalisation through logistic regression to compare the odds ratios respectively derived from survey and administrative data. Results: The extent of net under-reporting was moderately large in all three years amounting to about one-third of all inpatient episodes. However, there did not appear to be significant systematic biases in the degree of under-reporting by age or sex on stratified analyses and logistic regression modelling. Conclusion: Under-reporting was substantial in Hong Kong's THS. Recall bias was likely most responsible for such reporting inaccuracies. A proper full-design record-check study should be carried out to confirm the present findings. © 2005 Tsui et al; licensee BioMed Central Ltd., published_or_final_version

As yet, no one has written a comprehensive epidemiologic account of a severe acute respiratory syndrome (SARS) outbreak from an affected country.To provide a comprehensive epidemiologic account of a SARS outbreak from an affected territory.Epidemiologic analysis.The 2003 Hong Kong SARS outbreak.All 1755 cases and 302 deaths.Sociodemographic characteristics; infection clusters by time, occupation, setting, and workplace; and geospatial relationships were determined. The mean and variance in the time from infection to onset (incubation period) were estimated in a small group of patients with known exposure. The mean and variance in time from onset to admission, from admission to discharge, or from admission to death were calculated. Logistic regression was used to identify important predictors of case fatality.49.3% of patients were infected in clinics, hospitals, or elderly or nursing homes, and the Amoy Gardens cluster accounted for 18.8% of cases. The ratio of women to men among infected individuals was 5:4. Health care workers accounted for 23.1% of all reported cases. The estimated mean incubation period was 4.6 days (95% CI, 3.8 to 5.8 days). Mean time from symptom onset to hospitalization varied between 2 and 8 days, decreasing over the course of the epidemic. Mean time from onset to death was 23.7 days (CI, 22.0 to 25.3 days), and mean time from onset to discharge was 26.5 days (CI, 25.8 to 27.2 days). Increasing age, male sex, atypical presenting symptoms, presence of comorbid conditions, and high lactate dehydrogenase level on admission were associated with a greater risk for death.Estimates of the incubation period relied on statistical assumptions because few patients had known exposure times. Temporal changes in case management as the epidemic progressed, unavailable treatment information, and several potentially important factors that could not be thoroughly analyzed because of the limited sample size complicate interpretation of factors related to case fatality.This analysis of the complete data on the 2003 SARS epidemic in Hong Kong has revealed key epidemiologic features of the epidemic as it evolved.

We present an analysis of the first 10 weeks of the severe acute respiratory syndrome (SARS) epidemic in Hong Kong. The epidemic to date has been characterized by two large clusters—initiated by two separate “super-spread” events (SSEs)—and by ongoing community transmission. By fitting a stochastic model to data on 1512 cases, including these clusters, we show that the etiological agent of SARS is moderately transmissible. Excluding SSEs, we estimate that 2.7 secondary infections were generated per case on average at the start of the epidemic, with a substantial contribution from hospital transmission. Transmission rates fell during the epidemic, primarily as a result of reductions in population contact rates and improved hospital infection control, but also because of more rapid hospital attendance by symptomatic individuals. As a result, the epidemic is now in decline, although continued vigilance is necessary for this to be maintained. Restrictions on longer range population movement are shown to be a potentially useful additional control measure in some contexts. We estimate that most currently infected persons are now hospitalized, which highlights the importance of control of nosocomial transmission.

Despite the importance of fractures as an economic and health problem, and consequent interest in osteoporosis, few workers have previously attempted to define the overall incidence of fracture. This population based study was based in the Accident and Emergency Department of Cardiff Royal Infirmary and identified all patients presenting with fractures of any type. Over a single year a total of 6467 fractures were identified among the 306,600 people who live in the city of Cardiff. This gives an overall fracture incidence of 21.1/1000/year, (23.5/1000/year in males and 18.8/1000/year in females); a result very similar to those from similar work in the USA, Australia and Norway. This result is over twice the previous estimate of fracture incidence in the UK; the figure of 9/1000/year from the only equivalent study performed since the 1960s. In part, this discrepancy appears to reflect our more rigorous definition of the study population, and our improved ascertainment of minor fractures. We believe our result to offer the most accurate estimate of fracture incidence currently available for a UK population.

OBJECTIVE--To assess the health status of patients with 11 common illnesses--asthma, diabetes, arthritis, back pain, sciatica, hypertension, angina, anxiety, depression, and heart attack and stroke. DESIGN--Face to face interview using a structured questionnaire which contained the Short Form 36 questionnaire (SF-36) and questions on lifestyle, health service utilisation, and self reported conditions treated by physicians. SETTING--Patients' homes, in West Glamorgan, Wales. SUBJECTS--Twelve hundred adults, aged 20-89 years, were randomly selected from the register of the family health services authority. MAIN OUTCOME MEASURES--The eight scales within the SF-36 health profile. RESULTS--The response rate was 82%. Each illness had a distinctive profile; patients with anxiety or depression reported the worst health experience in role limitations because of emotional problems and mental health, while patients with back pain, arthritis, or sciatica registered the three highest negative scores in bodily pain and role limitations due to physical problems. For all disease groups, the general health perceptions of those with the disease was significantly worse than those without it (p < 0.01). CONCLUSIONS--The SF-36 allows comparison of the health status of patients suffering from different conditions. Data such as these can be used to inform better purchasing decisions on how resources might be more effectively deployed and as a bench mark to monitor the effects of multiple health care interventions by conducting serial surveys.

Objective Ribavirin and corticosteroids were used widely as front-line treatments for severe acute respiratory syndrome; however, previous evaluations were inconclusive. We assessed the effectiveness of ribavirin and corticosteroids as the initial treatment for severe acute respiratory syndrome using propensity score analysis. Methods We analyzed data on 1755 patients in Hong Kong and 191 patients in Toronto with severe acute respiratory syndrome using a generalized propensity score approach. Results The adjusted excess case fatality ratios of patients with severe acute respiratory syndrome receiving the combined therapy of ribavirin and corticosteroids within 2 days of admission, compared with those receiving neither treatment within 2 days of admission, were 3.8% (95% confidence interval, −1.5 to 9.2) in Hong Kong and 2.1% (95% confidence interval, −44.3 to 48.5) in Toronto. Conclusions Our results add strength to the hypothesis that the combination of ribavirin and corticosteroids has no therapeutic benefit when given early during severe acute respiratory syndrome infection. Further studies may investigate the effects of these treatments later in disease course.

Background. Hong Kong's rapidly ageing population, characterised by one of the longest life expectancies and the lowest fertility rate in the world, is likely to drive long-term care (LTC) expenditure higher. This study aims to identify key cost drivers and derive quantitative estimates of Hong Kong's LTC expenditure to 2036. Methods. We parameterised a macro actuarial simulation with data from official demographic projections, Thematic Household Survey 2004, Hong Kong's Domestic Health Accounts and other routine data from relevant government departments, Hospital Authority and other LTC service providers. Base case results were tested against a wide range of sensitivity assumptions. Results. Total projected LTC expenditure as a proportion of GDP reflected secular trends in the elderly dependency ratio, showing a shallow dip between 2004 and 2011, but thereafter yielding a monotonic rise to reach 3.0% by 2036. Demographic changes would have a larger impact than changes in unit costs on overall spending. Different sensitivity scenarios resulted in a wide range of spending estimates from 2.2% to 4.9% of GDP. The availability of informal care and the setting of formal care as well as associated unit costs were important drivers of expenditure. Conclusion. The "demographic window" between the present and 2011 is critical in developing policies to cope with the anticipated burgeoning LTC burden, in concert with the related issues of health care financing and retirement planning. © 2009 Chung et al., published_or_final_version