Different effects of meteorological factors on hand, foot and mouth disease in various climates: a spatial panel data model analysis

Socioeconomic, meteorological factors and spatiotemporal distribution of human brucellosis in China between 2004 and 2019-A study based on spatial panel model

BACKGROUND

Human brucellosis continues to be a great threat to human health in China. The present study aimed to investigate the spatiotemporal distribution of human brucellosis in China from 2004 to 2019, to analyze the socioeconomic factors, meteorological factors and seasonal effect affecting human brucellosis incidence in different geographical regions with the help of spatial panel model, and to provide a scientific basis for local health authorities to improve the prevention of human brucellosis.

METHODS

The monthly reported number and incidence of human brucellosis in China from January 2004 to December 2019 were obtained from the Data Center for China Public Health Science. Monthly average air temperature and monthly average relative humidity of 31 provincial-level administrative units (22 provinces, 5 autonomous regions and 4 municipalities directly under the central government) in China from October 2003 to December 2019 were obtained from the National Meteorological Science Data Centre. The inventory of cattle, the inventory of sheep, beef yield, mutton yield, wool yield, milk yield and gross pastoral product of 31 provincial-level administrative units in China from 2004 to 2019 were obtained from the National Bureau of Statistics of China. The temporal and geographical distribution of human brucellosis was displayed with Microsoft Excel and ArcMap software. The spatial autocorrelation and hotspot analysis was used to describe the association among different areas. Spatial panel model was constructed to explore the combined effects on the incidence of human brucellosis in China.

RESULTS

A total of 569,016 cases of human brucellosis were reported in the 31 provincial-level administrative units in China from January 2004 to December 2019. Human brucellosis cases were concentrated between March and July, with a peak in May, showing a clear seasonal increase. The incidence of human brucellosis in China from 2004 to 2019 showed significant spatial correlations, and hotspot analysis indicated that the high incidence of human brucellosis was mainly in the northern China, particularly in Inner Mongolia, Shanxi, and Heilongjiang. The results from spatial panel model suggested that the inventory of cattle, the inventory of sheep, beef yield, mutton yield, wool yield, milk yield, gross pastoral product, average air temperature (the same month, 2-month lagged and 3-month lagged), average relative humidity (the same month) and season variability were significantly associated with human brucellosis incidence in China.

CONCLUSIONS

The epidemic area of human brucellosis in China has been expanding and the spatial clustering has been observed. Inner Mongolia and adjacent provinces or autonomous regions are the high-risk areas of human brucellosis. The inventory of cattle and sheep, beef yield, mutton yield, wool yield, milk yield, gross pastoral product, average air temperature, average relative humidity and season variability played a significant role in the progression of human brucellosis. The present study strengthens the understanding of the relationship between socioeconomic, meteorological factors and the spatial heterogeneity of human brucellosis in China, through which 'One Health'-based strategies and countermeasures can be provided for the government to tackle the brucellosis menace.

The Spatial-Temporal Dimension of Oncological Prevalence and Mortality in Romania

The objective of this study was to identify spatial disparities in the distribution of cancer hotspots within Romania. Additionally, the research aimed to track prevailing trends in cancer prevalence and mortality according to a cancer type. The study covered the timeframe between 2008 and 2017, examining all 3,181 territorial administrative units. The analysis of spatial distribution relied on two key parameters. The first parameter, persistence, measured the duration for which cancer prevalence exceeded the 75th percentile threshold. Cancer prevalence refers to the total number of individuals in a population who have been diagnosed with cancer at a specific time point, including both newly diagnosed cases (occurrence) and existing cases. The second parameter, the time continuity of persistence, calculated the consecutive months during which cancer prevalence consistently surpassed the 75th percentile threshold. Notably, persistence of elevated values was also evident in lowland regions, devoid of any discernible direct connection to environmental conditions. In conclusion, this work bears substantial relevance to regional health policies, by aiding in the formulation of prevention strategies, while also fostering a deeper comprehension of the socioeconomic and environmental factors contributing to cancer.

Spatiotemporal associations between hand, foot and mouth disease and meteorological factors over multiple climate zones

Prior studies of hand, foot, and mouth disease (HFMD) have often observed inconsistent results regarding meteorological factors. We propose the hypothesis that these meteorological associations vary in regions because of the heterogeneity of their geographical characteristics. We have tested this hypothesis by applying a geographical detector and Bayesian space-time hierarchy model to measure stratified spatiotemporal heterogeneity and local associations between meteorological factors and HFMD risk in five climate zones in China from January 2016 to December 2017. We found a significant spatial stratified heterogeneity in HFMD risk and climate zone explained 15% of the spatial stratified heterogeneity. Meanwhile, there was a significant temporal stratified heterogeneity of 14% as determined by meteorological factors. Average temperatures and relative humidity had a significant positive effect on HFMD in all climate zones, they were the most obvious in the southern temperate zone. In northern temperate, southern temperate, northern subtropics, middle subtropics and southern subtropics climate zone, a 1 °C rise in temperature was related to an increase of 3.99%, 13.76%, 4.38%, 3.99%, and 7.74% in HFMD, and a 1% increment in relative humidity was associated with a 1.51%, 5.40%, 2.21%, 3.44%, and 4.78% increase, respectively. These findings provide strong support for our hypotheses that HFMD incidence has a significant spatiotemporal stratified heterogeneity and different climate zones have distinct influences on the disease. These findings provide strong support for our hypotheses: HFMD incidence had significant spatiotemporal stratified heterogeneity and different climate zones had distinct influences on it. The study suggested that HFMD prevention and policy should be made according to meteorological variation in each climate zone.

Spatiotemporally comparative analysis of three common infectious diseases in China during 2013-2015

BACKGROUND

Dengue fever (DF), influenza, and hand, foot, and mouth disease (HFMD) have had several various degrees of outbreaks in China since the 1900s, posing a serious threat to public health. Previous studies have found that these infectious diseases were often prevalent in the same areas and during the same periods in China.

METHODS

This study combined traditional descriptive statistics and spatial scan statistic methods to analyze the spatiotemporal features of the epidemics of DF, influenza, and HFMD during 2013-2015 in mainland China at the provincial level.

RESULTS

DF got an intensive outbreak in 2014, while influenza and HFMD were stable from 2013 to 2015. DF mostly occurred during August-November, influenza appeared during November-next March, and HFMD happened during April-November. The peaks of these diseases form a year-round sequence; Spatially, HFMD generally has a much higher incidence than influenza and DF and covers larger high-risk areas. The hotspots of influenza tend to move from North China to the southeast coast. The southeastern coastal regions are the high-incidence areas and the most significant hotspots of all three diseases.

CONCLUSIONS

This study suggested that the three diseases can form a year-round sequence in southern China, and the southeast coast of China is a particularly high-risk area for these diseases. These findings may have important implications for the local public health agency to allocate the prevention and control resources.

Effect of climate factors on the incidence of hand, foot, and mouth disease in Malaysia: A generalized additive mixed model

Climate change is one of the critical determinants affecting life cycles and transmission of most infectious agents, including malaria, cholera, dengue fever, hand, foot, and mouth disease (HFMD), and the recent Corona-virus pandemic. HFMD has been associated with a growing number of outbreaks resulting in fatal complications since the late 1990s. The outbreaks may result from a combination of rapid population growth, climate change, socioeconomic changes, and other lifestyle changes. However, the modeling of climate variability and HFMD remains unclear, particularly in statistical theory development. The statistical relationship between HFMD and climate factors has been widely studied using generalized linear and additive modeling. When dealing with time-series data with clustered variables such as HFMD with clustered states, the independence principle of both modeling approaches may be violated. Thus, a Generalized Additive Mixed Model (GAMM) is used to investigate the relationship between HFMD and climate factors in Malaysia. The model is improved by using a first-order autoregressive term and treating all Malaysian states as a random effect. This method is preferred as it allows states to be modeled as random effects and accounts for time series data autocorrelation. The findings indicate that climate variables such as rainfall and wind speed affect HFMD cases in Malaysia. The risk of HFMD increased in the subsequent two weeks with rainfall below 60 mm and decreased with rainfall exceeding 60 mm. Besides, a two-week lag in wind speeds between 2 and 5 m/s reduced HFMD's chances. The results also show that HFMD cases rose in Malaysia during the inter-monsoon and southwest monsoon seasons but fell during the northeast monsoon. The study's outcomes can be used by public health officials and the general public to raise awareness, and thus, implement effective preventive measures.

Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005-2017

Background

Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation.

Methodology/Principal findings

Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density (β = 2.844, P = 0.006), the number of health institutions per 1,000 residents (β = -0.095, P = 0.007), and the net migration rate (β = -0.219, P = 0.002).

Conclusions/Significance

Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth.

Syphilis is a sexually transmitted infection that continues to cause morbidity and mortality worldwide. The primary and secondary stages of syphilis are the most transmissive stages in the entire process of the disease. We analyzed primary and secondary (P&S) syphilis data from 2005 to 2017 in Guangzhou, China, provided by the National Notifiable Infectious Disease Reporting Information System. The results showed that the annual incidence rates of P&S syphilis slightly increased from 2005 to 2011 and then began to decrease in 2017. Cases of P&S syphilis were spatially clustered. The high-risk syphilis clusters tended to shift from developed areas to underdeveloped areas. There may be an inverted U-shaped relationship between the level of economic development and the incidence of P&S syphilis, suggesting that the incidence of P&S syphilis first increased before decreasing as the level of economic development increased further. These results emphasize the necessity of preventing syphilis at locations in the early stage of economic growth. Investments in syphilis prevention education for people in regions at early development stages may mitigate the increasing cost of syphilis to future healthcare systems.

Spatiotemporal clustering and meteorological factors affected scarlet fever incidence in mainland China from 2004 to 2017

OBJECTIVE

To analyze the spatiotemporal dynamic distribution and detect the related meteorological factors of scarlet fever from an ecological perspective, which could provide scientific information for effective prevention and control of this disease.

METHODS

The data on scarlet fever cases in mainland China were downloaded from the Data Center of the China Public Health Science, while monthly meteorological data were extracted from the official website of the National Bureau of Statistics. Global Moran's I, local Getis-Ord G_i^⁎ hotspot statistics, and Kulldorff's retrospective space-time scan statistical analysis were used to detect the spatial and spatiotemporal clusters of scarlet fever across all settings. A spatial panel data model was conducted to estimate the impact of meteorological factors on scarlet fever incidence.

RESULTS

Scarlet fever in China had obvious spatial, temporal, and spatiotemporal clustering, high-incidence spatial clusters were located mainly in the north and northeast of China. Nine spatiotemporal clusters were identified. A spatial lag fixed effects panel data model was the best fit for regression analysis. After adjusting for spatial individual effects and spatial autocorrelation (ρ = 0.5623), scarlet fever incidence was positively associated with a one-month lag of average temperature, precipitation, and total sunshine hours (all P-values < 0.05). Each 10 °C, 2 cm, and 10 h increase in temperature, precipitation, and sunshine hours, respectively, was associated with a 6.41% increment and 1.04% and 1.41% decrement in scarlet fever incidence, respectively.

CONCLUSION

The incidence of scarlet fever in China showed an upward trend in recent years. It had obvious spatiotemporal clustering, with the high-risk areas mainly concentrated in the north and northeast of China. Areas with high temperature and with low precipitation and sunshine hours tended to have a higher scarlet fever incidence, and we should pay more attention to prevention and control in these places.

Early warning of hand, foot, and mouth disease transmission: A modeling study in mainland, China

BACKGROUND

Hand, foot, and mouth disease (HFMD) is a global infectious disease; particularly, it has a high disease burden in China. This study was aimed to explore the temporal and spatial distribution of the disease by analyzing its epidemiological characteristics, and to calculate the early warning signals of HFMD by using a logistic differential equation (LDE) model.

METHODS

This study included datasets of HFMD cases reported in seven regions in Mainland China. The early warning time (week) was calculated using the LDE model with the key parameters estimated by fitting with the data. Two key time points, "epidemic acceleration week (EAW)" and "recommended warning week (RWW)", were calculated to show the early warning time.

RESULTS

The mean annual incidence of HFMD cases per 100,000 per year was 218, 360, 223, 124, and 359 in Hunan Province, Shenzhen City, Xiamen City, Chuxiong Prefecture, Yunxiao County across the southern regions, respectively and 60 and 34 in Jilin Province and Longde County across the northern regions, respectively. The LDE model fitted well with the reported data (R2 > 0.65, P < 0.001). Distinct temporal patterns were found across geographical regions: two early warning signals emerged in spring and autumn every year across southern regions while one early warning signals in summer every year across northern regions.

CONCLUSIONS

The disease burden of HFMD in China is still high, with more cases occurring in the southern regions. The early warning of HFMD across the seven regions is heterogeneous. In the northern regions, it has a high incidence during summer and peaks in June every year; in the southern regions, it has two waves every year with the first wave during spring spreading faster than the second wave during autumn. Our findings can help predict and prepare for active periods of HFMD.

The epidemic characteristics and spatial autocorrelation analysis of hand, foot and mouth disease from 2010 to 2015 in Shantou, Guangdong, China

BACKGROUND

Hand, foot and mouth disease (HFMD) is the highest incidence of infectious diseases in China. Shantou is one of the most infected cities. Therefore, it is necessary for us to understand the epidemic characteristics and distribution trend of HFMD in Shantou. The purpose of this study is to investigate the spatial epidemiological characteristics of HFMD and analyse its spatial autocorrelation.

METHOD

We collated and summarised the data of HFMD in Shantou from 2010 to 2015. SaTScan software and Moran's I were used to analyse the spatial correlation of HFMD, and the results were presented in ArcMap.

RESULTS

The distribution of HFMD in Shantou was of a seasonal trend, mainly concentrating during May and June. Children under 5-years-old were the main group of cases of HFMD, accounting for 92.46%. The proportion of infected children, especially those aged zero to 1, was the largest in each year, accounting for 45.62%, meaning that smaller children were more susceptible to HFMD. The number of male patients with HFMD was greater than that of females (1.78:1, male: female). With regard to the potential impact of patients' living style on the incidence rate of HFMD, this study revealed that scattered children were the dominant infected population, accounting for as much 84.49% of cases. The incidence of HFMD was unevenly distributed among streets. The incidence interval of streets was in a range of 13.76/100,000 to 1135.19/100,000. Spatial autocorrelation analysis showed that there was no global spatial correlation in Shantou, except in 2013. The results of local spatial autocorrelation analysis showed that H-H correlation existed in the high incidence local area of Shantou.

CONCLUSIONS

The incidence of HFMD across the various streets in Shantou not only varied widely but also represented local autocorrelation. Attention, as well as prevention and control measures, should be focused on those high-incidence areas, such as the Queshi street, Zhuchi street and Xinjin street.

Health impact of climate change in cities of middle-income countries: the case of China

BACKGROUND

This review examines the human health impact of climate change in China. Through reviewing available research findings under four major climate change phenomena, namely extreme temperature, altered rainfall pattern, rise of sea level and extreme weather events, relevant implications for other middle-income population with similar contexts will be synthesized.

SOURCES OF DATA

Sources of data included bilingual peer-reviewed articles published between 2000 and 2018 in PubMed, Google Scholar and China Academic Journals Full-text Database.

AREAS OF AGREEMENT

The impact of temperature on mortality outcomes was the most extensively studied, with the strongest cause-specific mortality risks between temperature and cardiovascular and respiratory mortality. The geographical focuses of the studies indicated variations in health risks and impacts of different climate change phenomena across the country.

AREAS OF CONTROVERSY

While rainfall-related studies predominantly focus on its impact on infectious and vector-borne diseases, consistent associations were not often found.

GROWING POINTS

Mental health outcomes of climate change had been gaining increasing attention, particularly in the context of extreme weather events. The number of projection studies on the long-term impact had been growing.

AREAS TIMELY FOR DEVELOPING RESEARCH

The lack of studies on the health implications of rising sea levels and on comorbidity and injury outcomes warrants immediate attention. Evidence is needed to understand health impacts on vulnerable populations living in growing urbanized cities and urban enclaves, in particular migrant workers. Location-specific climate-health outcome thresholds (such as temperature-mortality threshold) will be needed to support evidence-based clinical management plans and health impact mitigation strategies to protect vulnerable communities.

Impact of PM10 and meteorological factors on the incidence of hand, foot, and mouth disease in female children in Ningbo, China: a spatiotemporal and time-series study

Hand, foot, and mouth disease (HFMD) is a viral illness that is considered a critical public health challenge worldwide. Previous studies have demonstrated that meteorological parameters are significantly related to the incidence of HFMD in children; however, few studies have focused only on female children. This study quantified the associations of HFMD incidence with meteorological parameters and PM₁₀ (particulate matter with an aerodynamic diameter of 10 μm) among female children. Data were collected on daily HFMD cases, meteorological variables, and PM₁₀ levels in Ningbo, China, from January 2012 to December 2016. Data were assessed using a distributed lag nonlinear model (DLNM) with Poisson distribution. A total of 59,809 female children aged 0-15 years with HFMD were enrolled. The results showed that highest relative risk (RR) of HFMD for temperature was 3 °C and the lag effect was 3 days. The highest RR for PM₁₀ was 80 mg/m³ and the lag effect was 5 days. Spatial analysis showed that female HFMD incidence was mainly concentrated in the suburban of Ningbo city indicating that female children in this area should be more paid attention on avoiding this disease outbreak. Our findings suggest that HFMD prevention strategies should focus more attention on local meteorological parameters.

The Spatial and Temporal Research on the Coupling and Coordinated Relationship between Social Economy and Energy Environment in the Belt and Road Initiatives

The Belt and Road Initiative (BRI) was presented by China’s central government to achieve regional economic cooperation under the background of economic globalization. Energy and environmental problems, as by-products of economic success, are fundamental concerns in this grand project. An integrated method that combined the coupling coordinated degree model, Moran’s I, and the spatial panel data model was used in the research zone. Results of the coupling coordinated degree model indicated that the statuses of the social economy and the energy environment of the countries in the research zone improved from 1997 to 2014, with the changes in China and Eastern Europe being particularly significant. From the spatial econometric perspective, the coupling coordinated degrees of the countries in the research zone appeared in the spatial cluster in accordance with Moran’s I. The result of the spatial panel data model indicated that the coupling coordinated degree of one country positively affected those of its neighboring countries.

Short-term effects of meteorological factors and air pollution on childhood hand-foot-mouth disease in Guilin, China

BACKGROUND

Previous studies have always focused on the impact of various meteorological factors on Hand-foot-mouth disease (HFMD). However, only few studies have investigated the simultaneous effects of climate and air pollution on HFMD incidence.

METHODS

Daily HFMD counts among children aged 0-14 years in Guilin city were collected from 2014 to 2016. Distributed lag nonlinear models (DLNM) were used to assess the effects of extreme meteorological factors and air pollution indicators, as well as the effects of different lag days on HFMD incidence. Furthermore, this study explored the variability across gender and age groups.

RESULTS

Extreme temperatures, high precipitation and low-O₃ concentration increased the risk of HFMD. Hot effect was stronger and longer lasting than cold effect. Risks of rainy effect and low-O₃ effect continued to increase as lag days extended, with the maximum RR values: 1.60 (1.38, 1.86) (90th vs median) and 1.48 (1.16, 1.89) (1th vs median) at 0-14 lag days, respectively. By contrast, extremely high wind speed, low precipitation, low PM_2.5 and high O₃ exerted a certain protective effect on HFMD incidence. The corresponding minimum RR values were: 0.85 (0.74, 0.98) (90th vs median) at 0-14 lag days, 0.98 (0.97, 0.99) (10th vs median) at 0-14 lag days, 0.73 (0.61, 0.88) (1th vs median) at 0-14 lag days and 0.81 (0.73, 0.90) (99th vs median) at 0-7 lag days, respectively. Male children and children aged 0-1 years (followed by 1-3 years) were the most susceptible subgroups to extreme climatic effects and air pollution.

CONCLUSIONS

Our results indicated that daily meteorological factors and air pollution exert non-linear and delayed effects on pediatric HFMD, and such effects vary depending on gender and age. These findings may serve as a reference for the development of an early warning system and for the adoption of specific interventions for vulnerable groups.

Space-time heterogeneity of hand, foot and mouth disease in children and its potential driving factors in Henan, China

BACKGROUND

Hand, foot and mouth disease (HFMD) has become a substantial threat recently. However few studies have quantified spatiotemporal heterogeneity of HFMD and detected spatiotemporal interactive effect of potential driving factors on this disease.

METHODS

Using GeoDetector and Bayesian space-time hierarchy model, we characterized the epidemiology of HFMD in Henan, one of the largest population provinces in China, from 2012 to 2013, and quantified the impacts of potential driving factors.

RESULTS

Notably, 21.43 and 24.60% counties were identified as hot and cold spots, respectively. Spatially, the hotspots were mainly clustered in regions where the economic level was high. Temporally, the highest incidence period of HFMD was discovered to be in late spring and early summer. The impact of meteorological and socio-economic factors on the disease are significant, and this study found that a 1 °C rise in temperature was related to an increase of 4.09% in the HFMD incidence, a 1% increment in relative humidity was associated with a 1.77% increase of the disease, and a 1% increment in ratio of urban to rural population was associated with a 0.16% increase of the disease.

CONCLUSION

Meteorological and socio-economic factors presented significantly association with HFMD incidence, high-risk mainly appeared in large cities and their adjacent regions in hot and humid season. These findings will be helpful for HFMD risk control and disease-prevention policies implementation.

Geographical variations and influential factors in prevalence of cardiometabolic diseases in South Korea

Geographical variations and influential factors of disease prevalence are crucial information enabling optimal allocation of limited medical resources and prioritization of appropriate treatments for each regional unit. The purpose of this study was to explore the geographical variations and influential factors of cardiometabolic disease prevalence with respect to 230 administrative districts in South Korea. Global Moran’s I was calculated to determine whether the standardized prevalences of cardiometabolic diseases (hypertension, stroke, and diabetes mellitus) were spatially clustered. The CART algorithm was then applied to generate decision tree models that could extract the diseases’ regional influential factors from among 101 demographic, economic, and public health data variables. Finally, the accuracies of the resulting model–hypertension (67.4%), stroke (62.2%), and diabetes mellitus (56.5%)–were assessed by ten-fold cross-validation. Marriage rate was the main determinant of geographic variation in hypertension and stroke prevalence, which has the possibility that married life could have positive effects in lowering disease risks. Additionally, stress-related variables were extracted as factors positively associated with hypertension and stroke. In the opposite way, the wealth status of a region was found to have an influence on the prevalences of stroke and diabetes mellitus. This study suggested a framework for provision of novel insights into the regional characteristics of diseases and the corresponding influential factors. The results of the study are anticipated to provide valuable information for public health practitioners’ cost-effective disease management and to facilitate primary intervention and mitigation efforts in response to regional disease outbreaks.

Temperature and humidity affect the incidence of hand, foot, and mouth disease: a systematic review of the literature - a report from the International Society of Dermatology Climate Change Committee

Hand, foot, and mouth disease (HFMD) is an enterovirus-mediated condition that predominantly affects children under 5 years of age. The tendency for outbreaks to peak in warmer summer months suggests a relationship between HFMD and weather patterns. We reviewed the English-language literature for articles describing a relationship between meteorological variables and HFMD. Seventy-two studies meeting criteria were identified. A positive, statistically significant relationship was identified between HFMD cases and both temperature (61 of 67 studies, or 91.0%, reported a positive relationship) [CI 81.8-95.8%, P = 0.0001] and relative humidity (41 of 54 studies, or 75.9%) [CI 63.1-85.4%, P = 0.0001]. No significant relationship was identified between HFMD and precipitation, wind speed, and/or sunshine. Most countries reported a single peak of disease each year (most commonly early Summer), but subtropical and tropical climate zones were significantly more likely to experience a bimodal distribution of cases throughout the year (two peaks a year; most commonly late spring/early summer, with a smaller peak in autumn). The rising global incidence of HFMD, particularly in Pacific Asia, may be related to climate change. Weather forecasting might be used effectively in the future to indicate the risk of HFMD outbreaks and the need for targeted public health interventions.

Spatio-temporal analysis of the relationship between meteorological factors and hand-foot-mouth disease in Beijing, China

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Electronic supplementary material

The online version of this article (10.1186/s12879-018-3071-3) contains supplementary material, which is available to authorized users.

Meteorological factors and the incidence of mumps in Fujian Province, China, 2005-2013: Non-linear effects

BACKGROUND

Mumps is still an important public health issue in the world with several recent outbreaks. The seasonable distribution of the disease suggested that meteorological factors may influence the incidence of mumps. The aim of this study was to explore the possible association between meteorological factors and the incidence of mumps, and to provide scientific evidence to relevant health authorities for the disease control and prevention.

METHODS

We obtained the data of mumps cases and daily meteorological factors in Fujian Province in Eastern China over the period of 2005-2013. Using distributed lag non-linear model (DLNM) approach, we assessed the relationship between the meteorological factors and mumps incidence.

RESULTS

The effects of meteorological factors on the mumps incidence were all non-linear. Compared with the lowest risk values, the upper level of precipitation, atmospheric pressure and relative humidity could increase the risk of mumps, whereas the low level of wind velocity, temperature, diurnal temperature range and sunshine duration may also increase the risk. Moderate atmospheric pressure and low wind velocity had larger cumulative effects within 30lagdays and the relative risks were 10.02 (95%CI: 2.47-40.71) and 12.45 (95%CI: 1.40-110.78). For temperature, the cumulative effect within 30lagdays of minimum temperature was higher than that from maximum temperature in most populations. The cumulative effects of minimum temperature for males, children aged 10-14 and students were higher than those in other populations.

CONCLUSIONS

Meteorological factors, especially temperature and wind velocity, should be taken into consideration in the prevention and warning of possible mumps epidemic. Special attention should be paid to the vulnerable populations, such as teenagers and young adults.

The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison

•

A LASSO based forecast model for endemic infectious diseases is proposed.

•

Predictions at 4 weeks achieve desirable accuracy.

•

Models predict outbreaks but may struggle to predict outbreak size.

Introduction

Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response.

Methods

We assessed how the machine learning LASSO method may be useful in providing useful forecasts for different pathogens in countries with different climates. Separate LASSO models were constructed for different disease/country/forecast window with different model complexity by including different sets of predictors to assess the importance of different predictors under various conditions.

Results

There was a more apparent cyclicity for both climatic variables and incidence in regions further away from the equator. For most diseases, predictions made beyond 4 weeks ahead were increasingly discrepant from the actual scenario. Prediction models were more accurate in capturing the outbreak but less sensitive to predict the outbreak size. In different situations, climatic variables have different levels of importance in prediction accuracy.

Conclusions

For LASSO models used for prediction, including different sets of predictors has varying effect in different situations. Short term predictions generally perform better than longer term predictions, suggesting public health agencies may need the capacity to respond at short-notice to early warnings.

Monitoring hand, foot and mouth disease by combining search engine query data and meteorological factors

Hand, foot and mouth disease (HFMD) has been recognized as a significant public health threat and poses a tremendous challenge to disease control departments. To date, the relationship between meteorological factors and HFMD has been documented, and public interest of disease has been proven to be trackable from the Internet. However, no study has explored the combination of these two factors in the monitoring of HFMD. Therefore, the main aim of this study was to develop an effective monitoring model of HFMD in Guangzhou, China by utilizing historical HFMD cases, Internet-based search engine query data and meteorological factors. To this end, a case study was conducted in Guangzhou, using a network-based generalized additive model (GAM) including all factors related to HFMD. Three other models were also constructed using some of the variables for comparison. The results suggested that the model showed the best estimating ability when considering all of the related factors.

Spatiotemporal risk mapping of hand, foot and mouth disease and its association with meteorological variables in children under 5 years

Hand, foot and mouth disease (HFMD) risk has become an increasing concern in the Beijing–Tianjin–Hebei region, which is the biggest urban agglomeration in north-eastern Asia. In the study, spatiotemporal epidemiological features of HFMD were analysed, and a Bayesian space–time hierarchy model was used to detect local spatial relative risk (RR) and to assess the effect of meteorological factors. From 2009 to 2013, there was an obvious seasonal pattern of HFMD risk. The highest risk period was in the summer, with an average monthly incidence of 4·17/103, whereas the index in wintertime was 0·16/103. Meteorological variables influenced temporal changes in HFMD. A 1 °C rise in air temperature was associated with an 11·5% increase in HFMD (corresponding RR 1·122). A 1% rise in relative humidity was related to a 9·51% increase in the number of HFMD cases (corresponding RR 1·100). A 1 hPa increment in air pressure was related to a 0·11% decrease in HFMD (corresponding RR 0·999). A 1 h increase in sunshine was associated with a 0·28% rise in HFMD cases (corresponding RR 1·003). A 1 m/s rise in wind speed was related to a 6·2% increase in HFMD (corresponding RR 1·064). High-risk areas were mainly large cities, such as Beijing, Tianjin, Shijiazhuang and their neighbouring areas. These findings can contribute to risk control and implementation of disease-prevention policies.

Phylogeography of Coxsackievirus A16 Reveals Global Transmission Pathways and Recent Emergence and Spread of a Recombinant Genogroup

Coxsackievirus A16 (CV-A16; Picornaviridae) is an enterovirus (EV) type associated with hand, foot, and mouth disease (HFMD) in children. To investigate the spatial spread of CV-A16, we used viral sequence data sampled during a prospective sentinel surveillance of HFMD in France (2010 to 2014) and phylogenetic reconstruction. A data set of 168 VP1 sequences was assembled with 416 publicly available sequences of various geographic origins. The CV-A16 sequences reported were assigned to two clades, genogroup B and a previously uncharacterized clade D. The time origins of clades B and D were assessed in 1978 (1973 to 1981) and 2004 (2001 to 2007), respectively. The shape of the global CV-A16 phylogeny indicated worldwide cocirculation of genetically distinct virus lineages over time and across geographic regions. Phylogenetic tree topologies and Bayes factor analysis indicated virus migration. Virus transportation events in clade B within Europe and Asia and between countries of the two geographic regions were assessed. The sustained transmission of clade D viruses over 4 years was analyzed at the township level in France and traced back to Peru in South America. Comparative genomics provided evidence of recombination between CV-A16 clades B and D and suggested an intertype recombinant origin for clade D. Time-resolved phylogenies and HFMD surveillance data indicated that CV-A16 persistence is sustained by continuing virus migration at different geographic scales, from community transmission to virus transportation between distant countries. The results showed a significant impact of virus movements on the epidemiological dynamics of HFMD that could have implications for disease prevention.IMPORTANCE Coxsackievirus A16 is one of the most prevalent enterovirus types in hand, foot, and mouth disease outbreaks reported in Southeast Asia. This study is based on epidemiological and viral data on HFMD caused by CV-A16 in a European country. The phylogeographic data complemented the syndromic surveillance with virus migration patterns between geographic regions in France. The results show how viral evolutionary dynamics and global virus spread interact to shape the worldwide pattern of an EV disease. CV-A16 transmission is driven by movements of infected individuals at different geographic levels: within a country (local dynamics), between neighboring countries (regional dynamics), and between distant countries (transcontinental dynamics). The results are consistent with our earlier data on EV-A71 and confirm the epidemiological interconnection of Asia and Europe with regard to EV infections.