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ObjectivesTo examine the association among acute bronchiolitis-related hospitalisation in children, meteorological variation and outdoor air pollution.MethodsWe obtained the daily counts of acute bronchiolitis-related admission of children≤2 years old from all public hospitals, meteorological data and outdoor air pollutants’ concentrations between 1 January 2008 and 31 December 2017 in Hong Kong. We used quasi-Poisson generalised additive models together with distributed lag non-linear models to estimate the associations of interest adjusted for confounders.ResultsA total of 29 688 admissions were included in the analysis. Increased adjusted relative risk (ARR) of acute bronchiolitis-related hospitalisation was associated with high temperature (ambient temperature and apparent temperature) and was marginally associated with high vapour pressure, a proxy for absolute humidity. High concentration of NO2 was associated with elevated risk of acute bronchiolitis admission; the risk of bronchiolitis hospitalisation increased statistically significantly with cumulative NO2 exposure over the range 66.2–119.6 µg/m3. For PM10, the significant effect observed at high concentrations appears to be immediate but not long lasting. For SO2, ARR increased as the concentration approached the 75th percentile and then decreased though the association was insignificant.ConclusionsAcute bronchiolitis-related hospitalisation among children was associated with temperature and exposure to NO2 and PM10 at different lag times, suggesting a need to adopt sustainable clean air policies, especially to target pollutants produced by motor vehicles, to protect young children’s health.

To compare the incidences of early and late-onset neonatal sepsis, including group B streptococcus (GBS) and Escherichia coli (E. coli) before and after implementation of universal screening and intrapartum antibiotics prophylaxis (IAP).Retrospective cohort study.Eight public hospitals and 31 Maternal and Child Health Centres (in Hong Kong.460 552 women attending routine antenatal service from 2009 to 2020.Universal culture-based GBS screening has been offered to eligible women since 2012. Total births, GBS screening tests, maternal GBS colonisation and neonatal sepsis with positive blood or cerebrospinal fluid were retrieved from clinical and laboratory database.Maternal GBS colonisation rate, early- and late-onset neonatal sepsis (including GBS and E. coli).Of 318 740 women with universal culture-based screening, 63 767 women (20.0%) screened positive. After implementation of GBS screening and IAP, the incidence of early-onset neonatal sepsis decreased (3.25 versus 2.26 per 1000 live births, p 0.05), including those caused by GBS (1.03 versus 0.26 per 1000 live births, p 0.05). Segmented regression showed that change in early-onse GBS sepsis incidence after screening was the only significant variable in the outcome trend. There was no significant evidence of increase in incidence of late-onset neonatal sepsis including those caused by GBS.Universal culture-based GBS screening and IAP were associated with reduction in early-onset neonatal sepsis including GBS disease. Although an increase in incidence of late-onset neonatal sepsis including those caused by GBS cannot be totally ruled out, we did not identify significant evidence that this occurred.

Despite a conspicuous exacerbation of asthma among patients hospitalized due to influenza infection, no study has attempted previously to elucidate the relationship between environmental factors, influenza activity, and asthma simultaneously in adults. In this study, we examined this relationship using population-based hospitalization records over 22 years. Daily numbers of hospitalizations due to asthma in adults of 41 public hospitals in Hong Kong during 1998-2019 were obtained. The data were matched with meteorological records and air pollutant concentrations. We used type-specific and all-type influenza-like illness plus (ILI+) rates as proxies for seasonal influenza activity. Quasi-Poisson generalized additive models together with distributed-lag non-linear models were used to examine the association. A total of 212,075 hospitalization episodes due to asthma were reported over 22 years. The cumulative adjusted relative risk (ARR) of asthma hospitalizations reached 1.15 (95 % confidence interval [CI], 1.12-1.18) when the ILI+ total rate increased from zero to 20.01 per 1000 consultations. Compared with the median temperature, a significantly increased risk of asthma hospitalization (cumulative ARR = 1.10, 95 % CI, 1.05-1.15) was observed at the 5

Background Due to variations in climatic conditions, the effects of meteorological factors and PM2.5 on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM2.5. Methods A total of 20 165 laboratory‐confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi‐Poisson‐generalized additive model and the distributed lag non‐linear model to examine the relationship of interest, controlling for long‐term trends, seasonal trends, and holidays. Results A hockey‐stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (17.5 µg/m3). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM2.5, the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. Conclusions The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.

Summary 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.

While influenza infections and environmental factors have been documented as potential drivers of tuberculosis, no investigations have simultaneously examined their impact on tuberculosis at a population level. This study thereby made use of Hong Kong's surveillance data over 22 years to elucidate the temporal association between environmental influences, influenza infections, and tuberculosis activity.Weekly total numbers of hospital admissions due to tuberculosis, meteorological data, and outdoor air pollutant concentrations in Hong Kong during 1998-2019 were obtained. All-type influenza-like illness positive (ILI+) rate and type-specific ILI+ rates were used as proxies for influenza activity. Quasi-Poisson generalized additive models together with distributed lag non-linear models were used to assess the association of interest.A total of 164,116 hospital admissions due to tuberculosis were notified in public settings over a period of 22 years. The cumulative adjusted relative risk (ARR) of hospital admission due to tuberculosis was 1.07 (95% CI, 1.00-1.14) when the mean ambient temperature increased from 15.1 °C (the 5th percentile) to 24.5 °C (median). Short-term exposure to air pollutants was not found to be statistically significantly related to tuberculosis hospitalization. Accounting for the environmental covariates in the analysis, the cumulative ARR of tuberculosis admission was elevated to 1.05 (95% CI, 1.01-1.08) when the rate of ILI+ total increased from zero to 19.9 per 1000 consultations, the 95th percentile.Our findings demonstrated that increased influenza activity and higher temperature were related to a higher risk of tuberculosis admissions. Stepping up the promotion of influenza vaccination, especially before the summer season, may lower the risk of tuberculosis infection/reactivation for vulnerable groups (e.g. elderly born before the launch of Bacillus Calmette-Guérin vaccination programme).

The influences of weather and air pollutants on chronic obstructive pulmonary disease (COPD) have been well-studied. However, the heterogeneous effects of different influenza viral infections, air pollution and weather on COPD admissions and re-admissions have not been thoroughly examined. In this study, we aimed to elucidate the relationships between meteorological variables, air pollutants, seasonal influenza, and hospital admissions and re-admissions due to COPD in Hong Kong, a non-industrial influenza epicenter. A total number of 507703 hospital admissions (i.e., index admissions) and 301728 re-admission episodes (i.e., episodes within 30 days after the previous discharge) for COPD over 14 years (1998–2011) were obtained from all public hospitals. The aggregated weekly numbers were matched with meteorological records and outdoor air pollutant concentrations. Type-specific and all-type influenza-like illness positive (ILI+) rates were used as proxies for influenza activity. Generalized additive models were used in conjunction with distributed-lag non-linear models to estimate the associations of interest. According to the results, high concentrations of fine particulate matter, oxidant gases, and cold weather were strong independent risk factors of COPD outcomes. The cumulative adjusted relative risks exhibited a monotone increasing trend, except for ILI+ B, and the numbers were statistically significant over the entire observed range of ILI+ total and ILI+ A/H3N2 when the reference rate was zero. COPD hospitalization risk from influenza infection is higher in the elderly than that in the general population. In conclusion, our results suggest that health administrators should impose clean air policies, such as strengthening emissions control on petrol vehicles, to reduce pollution from oxidant gases and particulates. An extension of the influenza vaccination program for patients with COPD may need to be encouraged: for example, vaccination may be included in hospital discharge planning, particularly before the winter epidemic.

While many studies have focused on identifying the association between meteorological factors and the activity of COVID-19, we argue that the contribution of meteorological factors to a reduction of the risk of COVID-19 was minimal when the effects of control measures were taken into account. In this study, we assessed how much variability in COVID-19 activity is attributable to city-level socio-demographic characteristics, meteorological factors, and the control measures imposed. We obtained the daily incidence of COVID-19, city-level characteristics, and meteorological data from a total of 102 cities situated in 27 provinces/municipalities outside Hubei province in China from 1 January 2020 to 8 March 2020, which largely covers almost the first wave of the epidemic. Generalized linear mixed effect models were employed to examine the variance in the incidence of COVID-19 explained by different combinations of variables. According to the results, including the control measure effects in a model substantially raised the explained variance to 45%, which increased by >40% compared to the null model that did not include any covariates. On top of that, including temperature and relative humidity in the model could only result in < 1% increase in the explained variance even though the meteorological factors showed a statistically significant association with the incidence rate of COVID-19. In conclusion, we showed that very limited variability of the COVID-19 incidence was attributable to meteorological factors. Instead, the control measures could explain a larger proportion of variance., Author summary COVID-19 has a great impact worldwide, especially in some rural settings where healthcare resources are not sufficient. While control measures in these area may be limited, scholars have been discussing the potential effects of meteorological factors on mitigating COVID-19 transmission. Unfortunately, the majority of literatures only looked at the association between COVID-19 and environmental factors in which their findings could mislead readers that certain environmental conditions could be ‘protective’. In this study, we argue that the impact of the meteorological factors was very limited by using the incidence data from 102 Chinese cities in the first epidemic period when control measures have been taken into account. As what we expected, once the control measures have been incorporated in the modelling analysis, the meteorological factors could only explain < 1% increase in variability of COVID-19 while control measure explained the variance for more than 40% in total. Because of it, we suggest stringent control measures are necessary to control COVID-19 regardless the meteorological conditions of an area. Given that no vaccine is available to date, our investigation provides an additional evidence, as advocated by World Meteorological Organization rather than relying on changes in the natural environment for mitigation, active non-pharmaceutical interventions are necessary to curb the COVID-19 pandemic.

Despite high incidence of acute kidney injury (AKI) among patients hospitalised for influenza, no previous work has attempted to analyse and quantify the association between the two. Herein, we made use of Hong Kong's surveillance data to evaluate the time-varying relationship between seasonal influenza and risk of AKI with adjustment for potential environmental covariates. Generalized additive model was used in conjunction with distributed-lag non-linear model to estimate the association of interest with daily AKI admissions as outcome and daily influenza admissions as predictor, while controlling for environmental variables (i.e. temperature, relative humidity, total rainfall, nitrogen dioxide, and ozone). Results suggested a positive association between risk of AKI admission and number of influenza hospitalisation cases, with relative risk reaching 1.12 (95% confidence interval, 1.10-1.15) at the 95th percentile. Using median as reference, an almost U-shaped association between risk of AKI admission and temperature was observed; the risk increased significantly when the temperature was low. While ozone was not shown to be a risk factor for AKI, moderate-to-high levels of nitrogen dioxide (50-95th percentile) were significantly associated with increased risk of AKI admission. This study mentioned the possibility that AKI hospitalisations are subject to environmental influences and offered support for a positive association between seasonal influenza and AKI occurrence in Hong Kong. Authorities are urged to extend the influenza vaccination program to individuals with pre-existing renal conditions to safeguard the health of the vulnerable. Given that adverse health effects are evident at current ambient levels of nitrogen dioxide, the government is recommended to adopt clean-air policies at the earliest opportunity to protect the health of the community.

Compelling evidence suggests that phosphoprotein phosphatases (PPPs) are involved in a large spectrum of physiological and pathological processes, but little is known about their roles in pancreatic cancer. We investigated the expression level, prognostic value, and potential function of PPPs with data from Oncomine, GEPIA, THPA, and TCGA databases and an independent cohort of patients with pancreatic cancer. Among all the PPP catalytic subunits (PPPcs), the transcription levels of PPP1CA, PPP1CB, PPP3CA, PPP3CB, and PPP4C were higher in pancreatic cancer than in normal pancreas (P 2). Kaplan–Meier analysis showed that high transcription levels of PPP1CA, PPP1CB, PPP2CA, PPP2CB, PPP3CA, and PPP4C correlated with poorer survival. In contrast, patients with high levels of PPP3CB, PPP3CC, PPP5C, PPP6C, and PPEF2 had much better prognoses. Data from THPA and patients with pancreatic cancer enrolled in our hospital also confirmed the prognostic value of PPP1CA, PPP1CB, PPP2CA, PPP2CB, PPP3CA, PPP3CB, and PPP6C at the protein level. In addition, the Pearson Chi-square test showed that PPP3CB level was significantly correlated with T and N stages. GO and KEGG analyses showed that the genes and pathways related to the pathogenesis and progression of pancreatic cancer were greatly affected by alterations in PPPcs. Results of the present study suggest that PPP1CA, PPP1CB, PPP2CA, PPP2CB, and PPP3CA have deleterious effects but PPP3CB, PPP5C, and PPP6C have beneficial effects on pancreatic cancer.

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.

Background Since the first reported human infection with an avian-origin influenza A (H7N9) virus in China in early 2013, there have been recurrent outbreaks of the virus in the country. Previous studies have shown that meteorological factors are associated with the risk of human infection with the virus; however, their possible nonlinear and lagged effects were not commonly taken into account. Method To quantify the effect of meteorological factors on the risk of human H7N9 infection, daily laboratory-confirmed cases of human H7N9 infection and meteorological factors including total rainfall, average wind speed, average temperature, average relative humidity, and sunshine duration of the 11 sub-provincial/prefecture cities in Zhejiang during the first four outbreaks (13 March 2013–30 June 2016) were analyzed. Separate models were built for the 6 sub-provincial/prefecture cities with the greatest number of reported cases using a combination of logistic generalized additive model and distributed lag nonlinear models, which were then pooled by a multivariate meta-regression model to determine their overall effects. Results According to the meta-regression model, for rainfall, the log adjusted overall cumulative odds ratio was statistically significant when log of rainfall was >4.0, peaked at 5.3 with a value of 12.42 (95% confidence intervals (CI): [3.23, 21.62]). On the other hand, when wind speed was 2.1–3.0 m/s or 6.3–7.1 m/s, the log adjusted overall cumulative odds ratio was statistically significant, peaked at 7.1 m/s with a value of 6.75 (95% CI: [0.03, 13.47]). There were signs of nonlinearity and lag effects in their associations with the risk of infection. Conclusion As rainfall and wind speed were found to be associated with the risk of human H7N9 infection, weather conditions should be taken into account when it comes to disease surveillance, allowing prompt actions when an outbreak takes place.

Background The emerging cases of childhood scarlet fever (SF) and worsening air pollution problems in Chinese cities suggests a potential linkage between them. However, few studies had explored this association in a large childhood population. Methods We conducted a time-series analysis using the daily count of SF and the daily concentrations of particulate matters with an aerodynamic diameter of 2.5 (PM2.5) and 10 (PM10), as well as nitrogen dioxide (NO2) in Hangzhou, China from 2014 to 2018. Distributed lag nonlinear models were used to estimate the lag effects of PM2.5, PM10 and NO2 for a maximum lag of 10 days, which were quantified using relative risk (RR) comparing the adjusted risks at the 2.5th (extremely low effect) and 97.5th (extremely high effect) percentiles of concentration of the three air pollutants to that at the median. Stratified RRs by sex were also reported. Results Using the median concentration as reference, for extremely high effect, the RR was the highest on lag days 5, 6, and 3 for PM2.5, PM10, and NO2 respectively. While on lag day 0, the RR of PM2.5, PM10, and NO2 were 1.04 (95%CI: 0.90–1.20), 1.07 (95%CI: 0.92–1.24), and 1.08 (95%CI: 0.92–1.26) respectively, the RRs increased constantly and cumulatively to the maximum values of 1.88 (95%CI: 1.33–2.66), 1.82 (95%CI: 1.29–2.55), and 2.19 (95%CI: 1.47–3.27) for PM2.5, PM10, and NO2 respectively on lag day 10. Subgroup analyses showed that females appeared to be more vulnerable to the three pollutants than males. Conclusion Our study provides evidence that PM2.5, PM10, and NO2 exert delayed effects on SF infection.

Background Cold and dry conditions were well-documented as a major determinant of influenza seasonality in temperate countries but the association may not be consistent when the climate in temperate areas is closer to that in sub-tropical areas. We hypothesized latitudes may mediate the association between influenza activity and meteorological factors in 45 Japanese prefectures. Methods We used the weekly incidence of influenza-like illness of 45 prefectures from 2000 to 2018 as a proxy for influenza activity in Japan, a temperate country lying off the east coast of Asia. A combination of generalized additive model and distributed lag nonlinear model was adopted to investigate the associations between meteorological factors (average temperature, relative humidity, total rainfall, and actual vapour pressure, a proxy for absolute humidity) and the influenza incidence. Kendall’s tau b (τ) and Spearman correlation coefficient (rs) between latitude and the adjusted relative risk (ARR) of each meteorological factor were also assessed. Results A higher vapour pressure was significantly associated with a lower influenza risk but the ARR strongly weakened along with a lower latitude (τ = −0.23, p-value = 0.02; rs = −0.33, p-value = 0.03). Lower temperature and lower relatively humidity were significantly associated with higher influenza risks in over 65% and around 40% of the prefectures respectively but the strength and significance of the correlations between their ARRs and latitude were weaker than that from vapour pressure. Conclusion Even though the range of latitudes in Japan is small (26°N–43°N), the relationships between meteorological factors and influenza activity were mediated by the latitude. Our study echoed absolute humidity played a more important role in relating influenza risk, but we on the other hand showed its effect on influenza activity could be hampered in a low-latitude temperate region, which have a warmer climate. These findings thus offer a high-resolution characterization of the role of meteorological factors on influenza seasonality.

Hand, foot, and mouth disease (HFMD) is a common communicable disease among children and has been a global health problem in recent decades. Literature has shown that meteorological factors possibly drive the epidemic of HFMD, but the natures differ across regions. To elucidate the associations between meteorological factors and the epidemic of HFMD in Zhejiang province, China, the incidence rate and the number of probable and laboratory-confirmed cases of HFMD as well as meteorological factors (ambient temperature, relative humidity, total rainfall, wind speed, and total sunshine duration) during the year of 2013–2017 in the province were modelled by the Bayesian hierarchical Poisson spatiotemporal model with distributed lag nonlinear components, so as to capture spatiotemporal associations and potentially nonlinear or lagged effects of the meteorological factors. During the study period, there were altogether 689,898 HFMD cases in Zhejiang province, and the disease exhibited a strong spatiotemporal association. On average, Ningbo had the highest weekly incidence rate of 6.83/100,000. The cumulative adjusted relative risk (ARR) increased with average ambient temperature until 24.6 °C (ARR = 1.14, 95% CI: 1.04–1.30), at which the pattern reverted. The cumulative ARR also increased statistically significantly with average relative humidity. It was estimated that 1% increase in relative humidity corresponded to 1.07%–1.16% increase in ARR. Total rainfall, average wind speed, and total sunshine duration were not statistically significantly associated with the incidence rate. In conclusion, the existence of the associations between meteorological factors and the incidence rate of HFMD implies that the local government could make use of meteorological information for disease surveillance, allowing early preparation for the outbreak of HFMD when favorable conditions (wet and moderately hot) are forecasted, in order to reduce the heavy burden induced by the disease.

Human infection with the H7N9 virus has been reported recurrently since spring 2013. Given low pathogenicity of the virus in poultry, the outbreak cannot be noticed easily until a case of human infection is reported. Studies showed that the prevalence of influenza A subtype H7 in environmental samples is associated with the number of human H7N9 infection, with the latter associated with meteorological factors. Understanding the association between meteorological factors and the prevalence of H7 subtype in the environmental samples can shed light on how the virus propagates in the environment for disease control.Environmental samples and meteorological data (precipitation, temperature, relative humidity, sunshine duration, and wind speed) collected in Zhejiang province, China, during 2013-2017 were used. A Bayesian hierarchical binomial logistic spatiotemporal model which captures spatiotemporal effects was adopted to model the prevalence of H7 subtype with the meteorological factors.The monthly overall prevalence of H7 subtype in the environmental samples was usually30%. Compared with the odds at median, moderately low precipitation (49.19-115.60 mm), moderately long sunshine duration (4.22-9.25 h) and low temperature (9.33 °C) were statistically significantly associated with a higher adjusted odds of detecting an H7-positive sample, whereas moderately high precipitation (119.51-146.85 mm), short and moderately short sunshine duration (1.77 h; 4.00-4.17 h), and high temperature (23.09 °C) were statistically significantly associated with a lower adjusted odds. The adjusted odds increased multiplicatively by 1.11 per 1% increase in relative humidity.Since the prevalence of H7 subtype in environmental samples was associated with meteorological conditions and the number of human H7N9 infection, an environmental surveillance program which incorporates meteorological conditions in planning allows for early detection of the spread of the virus in the environment and better preparation for the outbreak in the human population.

Background Despite several immunization efforts, China saw a resurgence of measles in 2012. Monitoring of transmissions of individuals from different age groups could offer information that would be valuable for planning adequate disease control strategies. We compared the age-specific effective reproductive numbers (R) of measles during 2009-2016 in Guangdong, China. Methods We estimated the age-specific R values for 7 age groups: 0-8 months, 9-18 months, 19 months to 6 years, 7-15 years, 16-25 years, 26-45 years, and ≥46 years adapting the contact matrix of China. The daily numbers of laboratory and clinically confirmed cases reported to the Center for Disease Control and Prevention of Guangdong were used. Results The peak R values of the entire population were above unity from 2012 to 2016, indicating the persistence of measles in the population. In general, children aged 0-6 years and adults aged 26-45 years had larger values of R when comparing with other age groups after 2012. While the peaks of R values for children aged 0-6 years dropped steadily after 2013, the peaks of R values for adults aged 26-45 years kept at a high range every year. Conclusions Although the provincial supplementary immunization activities (SIAs) conducted in 2009 and 2010 were able to reduce the transmissions from 2009 to 2011, larger values of R for children aged 0-6 years were observed after 2012, indicating that the benefits of the SIAs were short-lived. In addition, the transmissions from adults aged between 26 and 45 years increased over time. Disease control strategies should target children and adult groups that carry high potential for measles transmission.

Breath mass spectrometry is a useful tool for identifying important compounds associated with health. However, there have been few studies that have explored human exhaled breath by full-scan mass spectrometry as a non-invasive method for medical diagnosis, which may be attributed to the difficulties resulting from multicollinearity and small sample sizes relative to a large number of product ions. In this study, breath samples from 54 chronic kidney disease patients were analyzed by selected ion flow tube mass spectrometry in the full-scan mode. With the signal intensities of product ions, we developed a novel and robust algorithm, iterative PCA with intensity screening (IPS), to build linear models for estimating important clinical parameters of chronic kidney disease. It has been shown that IPS provided good estimations in cross-validated samples, and furthermore the identified product ions could have direct medical relevance to the disease. The study demonstrated the potential of quantitative breath analysis using mass spectrometry for medical diagnosis, and the importance of applying appropriate statistical tools to unveil the rich information in this type of data.