Application of a low-cost, specific, and sensitive loop-mediated isothermal amplification (LAMP) assay to detect Plasmodium falciparum imported from Africa.

BACKGROUND: Chinese citizens traveling abroad bring back imported malaria cases to China. Current malaria diagnostic tests, including microscopy and antigen-detecting rapid tests, cannot reliably detect low-density infections. To complement existing diagnostic methods, we aimed to develop a new loop-mediated isothermal amplification (LAMP) assay to detect and identify Plasmodium falciparum in Chinese travelers returning from Africa. METHODS: We developed a miniaturized LAMP assay to amplify the actin I gene of P. falciparum. Each reaction consumed only 25% of the reagents used in a conventional LAMP assay and the same amount of DNA templates used in nested PCR. We evaluated this LAMP assay's performance and compared it to microscopy and a nested PCR assay using 466 suspected malaria cases imported from Africa. We assessed the sensitivity of the new LAMP assay using cultured P. falciparum, clinical samples, and a plasmid construct, allowing unprecedented precision when quantifying the limit of detection. RESULTS: The new LAMP assay was highly sensitive and detected two more malaria cases than nested PCR. Compared to nested PCR, the sensitivity and specificity of the novel LAMP assay were 100% [95% confidence interval (CI) 98.5-100%] and 99.1% (95% CI 96.7-99.9%), respectively. When evaluated using serial dilutions of the plasmid construct, the detection limit of the new LAMP was as low as 102 copies/µL, 10-fold lower than PCR. The LAMP assay detected 0.01 parasites/µL of blood (equal to 0.04 parasites/µL of DNA) using cultured P. falciparum and 1-7 parasites/µL of blood (4-28 parasites/µL of DNA) in clinical samples, which is as good as or better than previously reported and commercially licensed assays. CONCLUSION: The novel LAMP assay based on the P. falciparum actin I gene was specific, sensitive, and cost-effective, as it consumes 1/4 of the reagents in a typical LAMP reaction.

Age-specific disparity in life loss per death attributable to ambient temperature: A nationwide time-series study in China.

Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.

Urban-rural disparity of the short-term association of PM2.5 with mortality and its attributable burden.

Although studies have investigated the associations between PM2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014-2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM2.5 (lag 0-3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 µg/m3 increment in PM2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [-0.60%, 1.84%]). Disparities in PM2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM2.5 with mortality risks in China and demonstrated urban-rural disparities of PM2.5-mortality associations for various causes of death.

The association of compound hot extreme with mortality risk and vulnerability assessment at fine-spatial scale.

The frequency and intensity of compound hot extremes will be likely to increase in the context of global warming. Epidemiological studies have demonstrated the adverse effect of simple hot extreme events on mortality, but little is known about the effects of compound hot extremes on mortality. Daily meteorological, demographic, and mortality data during 2011-2017 were collected from 160 streets in Guangzhou City, China. We used distributed lag non-linear model (DLNM) to analyze the associations of different hot extremes with mortality risk in each street. Street-specific associations were then combined using a meta-analysis approach. To assess the spatial distribution of vulnerability to compound hot extremes, vulnerable characteristics at street level were selected using random forest model, and then we calculated and mapped spatial vulnerability index (SVI) at each street in Guangzhou. At street level, compared with normal day, compound hot extreme significantly increased mortality risk (relative risk(RR)=1.43, 95%CI:1.28-1.59) with higher risk for female (RR=1.54 [1.35-1.76]) and the elderly(RR for aged 65-74=1.41 [1.14-1.74]; RR for ≥75years=1.63 [1.45-1.84]) than male (RR=1.32 [1.15-1.52]) and population <65 years (RR=1.01 [0.83-1.22]). Areas with high vulnerability were in the urban center and the edge of suburban. High proportion of population over 64 years old in urban center, and high proportions of outdoor workers and population with illiteracy in suburban areas were the determinants of spatial vulnerability. We found that compound hot extreme significantly increased mortality risk at street level, which is modified by socio-economic and demographic factors. Our findings help allocate resources targeting vulnerable areas at fine-spatial scale.°.

Comparison of life loss per death attributable to ambient temperature among various development regions: a nationwide study in 364 locations in China.

BACKGROUND: Several studies have investigated the associations between ambient temperature and years of life lost (YLLs), but few focused on the difference of life loss attributable to temperature among different socioeconomic development levels. OBJECTIVES: We investigated the disparity in temperature-YLL rate relationships and life loss per death attributable to nonoptimal temperature in regions with various development levels. METHODS: Three hundred sixty-four Chinese counties or districts were classified into 92 high-development regions (HDRs) and 272 low-development regions (LDRs) according to socioeconomic factors of each location using K-means clustering approach. We used distributed lag non-linear models (DLNM) and multivariate meta-analysis to estimate the temperature-YLL rate relationships. We calculated attributable fraction (AF) of YLL and temperature-related average life loss per death to compare mortality burden of temperature between HDRs and LDRs. Stratified analyses were conducted by region, age, sex and cause of death. RESULTS: We found that non-optimal temperatures increased YLL rates in both HDRs and LDRs, but all subgroups in LDRs were more vulnerable. The disparity of cold effects between HDRs and LDRs was significant, while the difference in heat effect was insignificant. The overall AF of non-optimal temperature in LDRs [AF = 12.2, 95% empirical confidence interval (eCI):11.0-13.5%] was higher than that in HDRs (AF = 8.9, 95% eCI: 8.3-9.5%). Subgroups analyses found that most groups in LDRs had greater AFs than that in HDRs. The average life loss per death due to non-optimal temperature in LDRs (1.91 years, 95% eCI: 1.72-2.10) was also higher than that in HDRs (1.32 years, 95% eCI: 1.23-1.41). Most of AFs and life loss per death were caused by moderate cold in both HDRs and LDRs. CONCLUSIONS: Mortality burden caused by temperature was more significant in LDRs than that in HDRs, which means that more attention should be paid to vulnerable populations in LDRs in planning adaptive strategies.

Associations of ambient temperature exposure during pregnancy with the risk of miscarriage and the modification effects of greenness in Guangdong, China.

Miscarriage is one of the commonest complications of pregnancy. Although previous studies suggested that environmental factors were important causes of miscarriage, evidence is still inadequate. Here, we examined the association of maternal exposure to temperature with the risk of miscarriage and further assessed the modifying effects of surrounding residential greenness. A case-control study was conducted at a large hospital in Guangzhou, China. All participants' information was extracted from hospital records. An inverse distance weighted method was used to estimate the temperature exposure at each residential address, where the greenness was measured by Normalized Difference Vegetation Index (NDVI). A logistic regression model was applied to estimate the association of temperature exposure with the risk of miscarriage. A total of 2044 cases of miscarriage and 2285 controls were included in the present study. We observed a generally non-linear positive relationship between temperature exposure and the risk of miscarriage. More pronounced effects of high temperatures vs. low temperatures were found during the two months prior to hospitalization than in other periods. The odds ratio (OR) of 29.4 °C (95th centile) compared with 15 °C during the first month prior to hospitalization was 1.480 (95% CI: 1.021-2.145). Smaller effects of temperatures were seen on the risk of miscarriage among participants with moderately great surrounding greenness compared with those with less greenness. We concluded that maternal exposure to moderately high temperature during pregnancy may increase the risk of miscarriage, but the modifying effects of greenness on these associations need to be further tested in future studies.

Application of the analytic hierarchy approach to the risk assessment of Zika virus disease transmission in Guangdong Province, China.

BACKGROUND: An international spread of Zika virus (ZIKV) infection has attracted global attention in 2015. The infection also affected Guangdong province, which is located in southern China. Multiple factors, including frequent communication with South America and Southeast Asia, suitable climate (sub-tropical) for the habitat of Aedes species, may increase the risk of ZIKV disease transmission in this region. METHODS: An analytic hierarchy process (AHP) method was used to develop a semi-quantitative ZIKV risk assessment model. After selecting indicators, we invited experts in related professions to identify the index weight and based on that a hierarchical structure was generated. Then a series of pairwise comparisons were used to determine the relative importance of the criteria. Finally, the optimal model was established to estimate the spatial and seasonal transmission risk of ZIKV. RESULTS: A total of 15 factors that potentially influenced the risk of ZIKV transmission were identified. The factor that received the largest weight was epidemic of ZIKV in Guangdong province (combined weight [CW] =0.37), followed by the mosquito density (CW = 0.18) and the epidemic of DENV in Guangdong province (CW = 0.14). The distribution of 123 districts/counties' RIs of ZIKV in Guangdong through different seasons were presented, respectively. CONCLUSIONS: Higher risk was observed within Pearl River Delta including Guangzhou, Shenzhen and Jiangmen, and the risk is greater in summer and autumn compared to spring and winter.

Disease Burden from Hepatitis B Virus Infection in Guangdong Province, China.

OBJECTIVE: To estimate the disease burden and financial burden attributed to hepatitis B virus (HBV) infection in Guangdong Province. METHODS: Based on the data of incidence, mortality and healthcare cost of HBV-related diseases and other socio-economic data in Guangdong Province, we estimated deaths, disability-adjusted life-years (DALYs) and economic cost for the three HBV-related diseases-hepatitis B, liver cirrhosis and liver cancer-in Guangdong following the procedures developed for the global burden of disease study. Then disease burden and economic cost attributed to HBV infection was estimated. RESULTS: HBV infection was estimated to have caused 33,600 (95% confidence interval (CI): 29,300-37,800) premature deaths and the loss of 583,200 (95% CI: 495,200-671,100) DALYs in Guangdong in 2005. The greatest loss of deaths and DALYs were from liver cancer. The 45-59 years age group had the greatest burden attributable to HBV infection. The estimated total annual cost of HBV-related diseases in Guangdong was RMB 10.8 (95% CI: 8.7-13.0) billion, the direct and indirect cost were RMB 2.6 (95% CI: 2.1-3.2) and 8.2 (95% CI: 6.6-9.8) billion. CONCLUSIONS: HBV infection is a great medical challenge as well as a significant economic burden to Guangdong Province. The results suggest that substantial health benefits could be gained by extending effective public health and clinical interventions to reduce HBV infection in Guangdong Province.

Individual-level and community-level effect modifiers of the temperature-mortality relationship in 66 Chinese communities.

OBJECTIVES: To examine the modification of temperature-mortality association by factors at the individual and community levels. DESIGN AND METHODS: This study investigated this issue using a national database comprising daily data of 66 Chinese communities for 2006-2011. A 'threshold-natural cubic spline' distributed lag non-linear model was utilised to estimate the mortality effects of daily mean temperature, and then examined the modification of the relationship by individual factors (age, sex, education level, place of death and cause of death) using a meta-analysis approach and community-level factors (annual temperature, population density, sex ratio, percentage of older population, health access, household income and latitude) using a meta-regression method. RESULTS: We found significant effects of high and low temperatures on mortality in China. The pooled excess mortality risk was 1.04% (95% CI 0.90% to 1.18%) for a 1°C temperature decrease below the minimum mortality temperature (MMT), and 3.44% (95% CI 3.00% to 3.88%) for a 1°C temperature increase above MMT. At the individual level, age and place of death were found to be significant modifiers of cold effect, while age, sex, place of death, cause of death and education level were effect modifiers of heat effect. At the community level, communities with lower socioeconomic status and higher annual temperature were generally more vulnerable to the mortality effects of high and low temperatures. CONCLUSIONS: This study identifies susceptibility based on both individual-level and community-level effect modifiers; more attention should be given to these vulnerable individuals and communities to reduce adverse health effects of extreme temperatures.

[Analysis of the impact of the socio-economic factors on temperature-mortality association in southern China].

OBJECTIVE: To explore the impact of the socio-economic factors on the temperature-mortality association in different cities in southern China. METHODS: Daily mortality registration data, meteorological data and air pollution data of the cities as Changsha and Kunming during 2006-2009, and cities as Guangzhou and Zhuhai during 2006-2010, were collected to explore modifying effects, stratified by age, gender, education and place of death, of socio-economic factors on the association between temperature and mortality, by distributed lag non-linear model. The accumulative effect of temperature-mortality were separately analyzed in each city, under the high temperature (0-3 days) and low temperature (0-20 days) situation. The association between temperature and mortality was evaluated by general linear threshold model. The above process was firstly adopted to analyze the impact in single city and then Meta analysis was applied to analyze the impact in several cities by effect-combine. RESULTS: The relationship between temperature and mortality in the four cities showed nonlinearity. The minimum mortality risk was separately 23.5 °C, 20.5 °C, 25.0 °C and 26.0 °C in Changsha, Kunming, Guangzhou and Zhuhai. The results of effect-combine showed that low-temperature (RR = 1.67, 95%CI:1.54-1.80) has a higher gross effect than high-temperature (RR = 1.11, 95%CI:1.01-1.18) on population. With the age increasing, risk of death increased both under high and low temperature situation, and the effect of low temperature was greater (RR = 1.83, 95%CI:1.65-2.04) for the elderly than it of high temperature (RR = 1.17, 95%CI:1.03-1.33). The mortality risk among females (cold and hot effects(95%CI) were 1.75(1.57-1.97) and 1.11(0.99-1.25), respectively)was higher than it among males (cold and hot effects(95%CI) were 1.59(1.45-1.77) and 1.11(1.03-1.19), respectively). Whereas the mortality risk on higher education population was significantly higher (cold and hot effects (95%CI) were 1.89(1.48-2.45)and 1.34(1.19-1.48), respectively) than it on other educated people. CONCLUSION: Age, gender, educational level and place of death showed modifying effects on the association between temperature and mortality. The elderly, women and highly educated people were vulnerable to the temperature influence on mortality.