Archie C. A. Clements

Influenza and pneumococcal vaccine uptake in the older population aged 65 years or over of Hong Kong dramatically increased since the 2003 SARS outbreak. This study is aimed to evaluate the impact of increased coverage of influenza and pneumococcal vaccines by comparing the change of disease burden in the older population of Hong Kong, with the burden in the older population of Brisbane with relatively high vaccine coverage in the past fifteen years. Time series segmented regression models were applied to weekly numbers of cause-specific mortality or hospitalization of Hong Kong and Brisbane. Annual excess rates of mortality or hospitalization associated with influenza in the older population were estimated for the pre-SARS (reference period), post-SARS and post-pandemic period, respectively. The rate ratios (RRs) between these periods were also calculated to assess the relative change of disease burden. Compared to the pre-SARS period, excess rates of mortality associated with influenza during the post-SARS period in Hong Kong decreased for cardiorespiratory diseases (RR = 0.90, 95% CI 0.80, 1.01), stroke (RR = 0.74, 95% CI 0.50, 1.09), and ischemic heart diseases (RR = 0.45, 95% CI 0.34, 0.58). The corresponding RRs in Brisbane were 0.79 (95% CI 0.54, 1.15), 0.33 (0.13, 0.80), and 1.09 (0.62, 1.90), respectively. Only the mortality of ischemic heart diseases showed a greater reduction in Hong Kong than in Brisbane. During the post-pandemic period, excess rates of all-cause mortality increased in Hong Kong, but to a lesser extent than in Brisbane (RR = 1.41 vs 2.39). A relative decrease (or less of an increase) of influenza disease burden was observed in the older population of Hong Kong after increased coverage of influenza and pneumococcal vaccines in this population, as compared to those of Brisbane where vaccination rates remained stable. The lack of significant findings in some disease categories highlights the challenges of evaluating the benefits of vaccination at the population level.

Cystic echinococcosis (CE) and alveolar echinococcosis (AE) are highly endemic in Xiji County of Ningxia Hui Autonomous Region (NHAR) in China where the control campaign based on dog de-worming with praziquantel has been undertaken over preceding decades. This study is to determine the current prevalence of Echinococcus granulosus and E. multilocularis in domestic dogs and monitor the echinococcosis transmission dynamics. Study villages were selected using landscape patterns (Geographic Information System, GIS) for Echinococcus transmission “hot spots”, combined with hospital records identifying risk areas for AE and CE. A survey of 750 domestic dogs, including copro-sampling and owner questionnaires, from 25 selected villages, was undertaken in 2012. A copro-multiplex PCR assay was used for the specific diagnosis of E. granulosus and E. multilocularis in the dogs. Data analysis, using IBM SPSS Statistics, was undertaken, to compare the prevalence of the two Echinococcus spp. in dogs between four geographical areas of Xiji by the χ2 test. Univariate analysis of the combinations of outcomes from the questionnaire and copro-PCR assay data was carried out to determine the significant risk factors for dog infection. The highest de-worming rate of 84.0% was found in the northwest area of Xiji County, and significant differences (P < 0.05) in the de-worming rates among dogs from the four geographical areas of Xiji were detected. The highest prevalence (19.7%, 59/300) of E. multilocularis occurred in northwest Xiji, though the highest prevalence (18.1%, 38/210) of E. granulosus occurred in southwest Xiji. There was no significant difference (P > 0.05) in the prevalence of E. granulosus in dogs from the northwest, southwest, northeast, and southeast of Xiji, but there were significant differences (P < 0.05) between dogs infected with E. multilocularis from the four areas. None of the other independent variables was statistically significant. The results from this study indicate a high prevalence of both E. granulosus and E. muiltilocularis in dogs in Xiji County, NHAR. Transmission of E. multilocularis was more impacted by geographical risk-factors in Xiji County than that of E. granulosus. Dogs have the potential to maintain the transmission of both species of Echinococcus within local Xiji communities, and the current praziquantel dosing of dogs appears to be ineffective or poorly implemented in this area.

Member countries in the Asia Pacific Malaria Elimination Network (APMEN) are pursuing the global goal of malaria elimination by 2030. Different countries are in various phases of malaria elimination and this review aims to present a compilation of available evidence on the challenges and way forward for malaria elimination in APMEN countries. Malaria transmission in these States is complex. APMEN member countries include the largest populations living in areas of malaria transmission risk outside Africa. They are a global source for spread of artemisinin-based combination therapy (ACT) resistance, include the biggest burden of Plasmodium vivax and zoonotic malaria, and face many geopolitical and socio-economic factors that will challenge malaria elimination efforts. These challenges can be addressed in part through operational research to identify country-specific solutions, making better use of operational data such as through spatial decision support system (SDSS) approaches, strengthening surveillance, and cross-border initiative for coordinated action.

Hand-foot-mouth disease (HFMD) is a common infectious disease in China and occurs mostly in infants and children. Beijing is a densely populated megacity, in which HFMD has been increasing in the last decade. The aim of this study was to quantify spatio-temporal characteristics of HFMD and the relationship between meteorological factors and HFMD incidence in Beijing, China. Daily counts of HFMD cases from January 2010 to December 2012 were obtained from the Beijing Center for Disease Prevention and Control (CDC). Seasonal trend decomposition with Loess smoothing was used to explore seasonal patterns and temporal trends of HFMD. Bayesian spatiotemporal Poisson regression models were used to quantify spatiotemporal patterns of HFMD incidence and associations with meteorological factors. There were 114,777 HFMD cases reported to Beijing CDC from 1 January 2010 to 31 December 2012 and the raw incidence was 568.6 per 100,000 people. May to July was the peak period of HFMD incidence each year. Low-incidence townships were clustered in central, northeast and southwest regions of Beijing. Mean temperature, relative humidity, wind velocity and sunshine hours were all positively associated with HFMD. The effect of wind velocity was significant with a RR of 3.30 (95%CI: 2.37, 4.60) per meter per second increase, as was sunshine hours with a RR of 1.20 (95%CI: 1.02, 1.40) per 1 hour increase. The distribution of HFMD in Beijing was spatiotemporally heterogeneous, and was associated with meteorological factors. Meteorological monitoring could be incorporated into prediction and surveillance of HFMD in Beijing.

Malaria causes significant morbidity and mortality worldwide. There are several preventive measures that are currently employed, including insecticide-treated nets (ITNs, including long-lasting insecticidal nets and insecticidal-treated bed nets), indoor residual spraying (IRS), prophylactic drugs (PD), and untreated nets (UN). However, it is unclear which measure is the most effective for malaria prevention. We therefore undertook a network meta-analysis to compare the efficacy of different preventive measures on incidence of malaria infection. A systematic literature review was undertaken across four medical and life sciences databases (PubMed, Cochrane Central, Embase, and Web of Science) from their inception to July 2016 to compare the effectiveness of different preventive measures on malaria incidence. Data from the included studies were analysed for the effectiveness of several measures against no intervention (NI). This was carried out using an automated generalized pairwise modeling (GPM) framework for network meta-analysis to generate mixed treatment effects against a common comparator of no intervention (NI). There were 30 studies that met the inclusion criteria from 1998–2016. The GPM framework led to a final ranking of effectiveness of measures in the following order from best to worst: PD, ITN, IRS and UN, in comparison with NI. However, only ITN (RR: 0.49, 95% CI: 0.32–0.74) showed precision while other methods [PD (RR: 0.24, 95% CI: 0.004–15.43), IRS (RR: 0.55, 95% CI: 0.20–1.56) and UN (RR: 0.73, 95% CI: 0.28–1.90)] demonstrating considerable uncertainty associated with their point estimates. Current evidence is strong for the protective effect of ITN interventions in malaria prevention. Even though ITNs were found to be the only preventive measure with statistical support for their effectiveness, the role of other malaria control measures may be important adjuncts in the global drive to eliminate malaria.

Human echinococcoses are parasitic helminth infections that constitute a serious public health concern in several regions across the world. Cystic (CE) and alveolar echinococcosis (AE) in China represent a high proportion of the total global burden of these infections. This study was conducted to predict the spatial distribution of human seropositivity for Echinococcus species in Xiji County, Ningxia Hui Autonomous Region (NHAR), with the aim of identifying communities where targeted prevention and control efforts are required. Bayesian geostatistical models with environmental and demographic covariates were developed to predict spatial variation in the risk of human seropositivity for Echinococcus granulosus (the cause of CE) and E. multilocularis (the cause of AE). Data were collected from three cross-sectional surveys of school children conducted in Xiji County in 2002–2003, 2006–2007 and 2012–2013. Environmental data were derived from high-resolution satellite images and meteorological data. The overall seroprevalence of E. granulosus and E. multilocularis was 33.4 and 12.2%, respectively, across the three surveys. Seropositivity for E. granulosus was significantly associated with summer and winter precipitation, landscape fragmentation variables and the extent of areas covered by forest, shrubland, water and bareland/artificial surfaces. Seropositivity for E. multilocularis was significantly associated with summer and winter precipitations, landscape fragmentation variables and the extent of shrubland and water bodies. Spatial correlation occurred over greater distances for E. granulosus than for E. multilocularis. The predictive maps showed that the risk of seropositivity for E. granulosus expanded across Xiji during the three surveys, while the risk of seropositivity for E. multilocularis became more confined in communities located in the south. The identification of high-risk areas for seropositivity for these parasites, and a better understanding of the role of the environment in determining the transmission dynamics of Echinococcus spp. may help to guide and monitor improvements in human echinococcosis control strategies by allowing targeted allocation of resources.

Human cystic (CE) and alveolar (AE) echinococcoses are zoonotic parasitic diseases that can be influenced by environmental variability and change through effects on the parasites, animal intermediate and definitive hosts, and human populations. We aimed to assess and quantify the spatiotemporal patterns of human echinococcoses in Ningxia Hui Autonomous Region (NHAR), China between January 1994 and December 2013, and examine associations between these infections and indicators of environmental variability and change, including large-scale landscape regeneration undertaken by the Chinese authorities. Data on the number of human echinococcosis cases were obtained from a hospital-based retrospective survey conducted in NHAR for the period 1 January 1994 through 31 December 2013. High-resolution imagery from Landsat 4/5-TM and 8-OLI was used to create single date land cover maps. Meteorological data were also collected for the period January 1980 to December 2013 to derive time series of bioclimatic variables. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between annual cases of CE and AE and environmental variables. Annual CE incidence demonstrated a negative temporal trend and was positively associated with winter mean temperature at a 10-year lag. There was also a significant, nonlinear effect of annual mean temperature at 13-year lag. The findings also revealed a negative association between AE incidence with temporal moving averages of bareland/artificial surface coverage and annual mean temperature calculated for the period 11–15 years before diagnosis and winter mean temperature for the period 0–4 years. Unlike CE risk, the selected environmental covariates accounted for some of the spatial variation in the risk of AE. The present study contributes towards efforts to understand the role of environmental factors in determining the spatial heterogeneity of human echinococcoses. The identification of areas with high incidence of CE and AE may assist in the development and refinement of interventions for these diseases, and enhanced environmental change risk assessment.

Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease. Notifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran’s I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling. The analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ≥ 14 years were found to be 74% [95% credible interval (CrI): 72–76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4–21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6–0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29–59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables. Dengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection.