Using Geographically Weighted Regression to Study the Seasonal Influence of Potential Risk Factors on the Incidence of HFMD on the Chinese Mainland

Hand, foot, and mouth disease (HFMD) is an epidemic infectious disease in China. Its incidence is affected by a variety of natural environmental and socioeconomic factors, and its transmission has strong seasonal and spatial heterogeneity. To quantify the spatial relationship between the incidence of HFMD (I-HFMD) and eight potential risk factors (temperature, humidity, precipitation, wind speed, air pressure, altitude, child population density, and per capita GDP) on the Chinese mainland, we established a geographically weighted regression (GWR) model to analyze their impacts in different seasons and provinces. The GWR model successfully describes the spatial changes of the influence of potential risks, and shows greatly improved estimation performance compared with the ordinary linear regression (OLR) method. Our findings help to understand the seasonally and spatially relevant effects of natural environmental and socioeconomic factors on the I-HFMD, and can provide information to be used to develop effective prevention strategies against HFMD at different locations and in different seasons.

Download Full-text

Modeling Malaria Incidence Associated with Environmental Risk Factors in Ethiopia using the Geographically Weighted Regression Model, 2015-2016

10.21203/rs.3.rs-907839/v1 ◽

2021 ◽

Author(s):

Berhanu Berga Dadi

Keyword(s):

Risk Factors ◽

Relative Humidity ◽

Spatial Patterns ◽

Environmental Risk ◽

Geographically Weighted Regression ◽

Malaria Incidence ◽

Environmental Risk Factors ◽

Weighted Regression ◽

Study Results ◽

Gwr Model

Abstract Background: In Ethiopia, still, malaria is killing and affecting a lot of people of any age group somewhere in the country at any time. However, due to limited research, little is known about the spatial patterns and correlated risk factors on the wards scale. Methods: In this research, we explored spatial patterns and evaluated related potential environmental risk factors in the distribution of malaria incidence in Ethiopia in 2015 and 2016. Hot Spot Analysis (Getis-Ord Gi* statistic) was used to assess the clustering patterns of the disease. The ordinary least square (OLS), geographically weighted regression (GWR), and semiparametric geographically weighted regression (s-GWR) models were compared to describe the spatial association of potential environmental risk factors with malaria incidence.Results: Our results revealed a heterogeneous and highly clustered distribution of malaria incidence in Ethiopia during the study period. The s-GWR model best explained the spatial correlation of potential risk factors with malaria incidence and was used to produce predictive maps. The GWR model revealed that the relationship between malaria incidence and elevation, temperature, precipitation, relative humidity, and normalized difference vegetation index (NDVI) varied significantly among the wards. During the study period, the s-GWR model provided a similar conclusion, except in the case of NDVI in 2015, and elevation and temperature in 2016, which were found to have a global relationship with malaria incidence. Hence, precipitation and relative humidity exhibited a varying relationship with malaria incidence among the wards in both years. Conclusions: This finding could be used in the formulation and execution of evidence-based malaria control and management program to allocate scare resources locally at the wards level. Moreover, these study results provide a scientific basis for malaria researchers in the country.

Download Full-text

Integration of a Kalman filter in the geographically weighted regression for modeling the transmission of hand, foot and mouth disease

10.21203/rs.2.15522/v1 ◽

2019 ◽

Author(s):

Bisong Hu ◽

Wenqing Qiu ◽

Chengdong Xu ◽

Jinfeng Wang

Keyword(s):

Kalman Filter ◽

Socioeconomic Factors ◽

Potential Risk ◽

Geographically Weighted Regression ◽

Foot And Mouth Disease ◽

Mouth Disease ◽

Spatiotemporal Patterns ◽

Weighted Regression ◽

Estimation Accuracy ◽

Determinant Factors

Abstract Background: Hand, foot and mouth disease (HFMD) is a common infectious disease whose mechanism of transmission continues to remain a puzzle for researchers. The measurement and prediction of the HFMD incidence can be combined to improve the estimation accuracy, and provide a novel perspective to explore the spatiotemporal patterns and determinant factors of an HFMD epidemic. Methods: In this study, we collected weekly HFMD incidence reports for a total of 138 districts in Shandong province, China, from May 2008 to March 2009. A Kalman filter was integrated with geographically weighted regression (GWR) to estimate the HFMD incidence. Spatiotemporal variation characteristics were explored and potential risk regions were identified, along with quantitatively evaluating the influence of meteorological and socioeconomic factors on the HFMD incidence. Results: The results showed that the average error covariance of the estimated HFMD incidence by district was reduced from 0.3841 to 0.1846 compared to the measured incidence, indicating an overall improvement of over 50% in error reduction. Furthermore, three specific categories of potential risk regions of HFMD epidemics in Shandong were identified by the filter processing, with manifest filtering oscillations in the initial, local and long-term periods, respectively. Amongst meteorological and socioeconomic factors, the temperature and number of hospital beds per capita, respectively, were recognized as the dominant determinants that influence HFMD incidence variation. Conclusions: The estimation accuracy of the HFMD incidence can be significantly improved by integrating a Kalman filter with GWR and the integration is effective for exploring spatiotemporal patterns and determinants of an HFMD epidemic. Our findings could help establish more accurate HFMD prevention and control strategies in Shandong. The present study demonstrates a novel approach to exploring spatiotemporal patterns and determinant factors of HFMD epidemics, and it can be easily extended to other regions and other infectious diseases similar to HFMD.

Download Full-text

Premature Arterial Disease Associated with Familial Antithrombin III Deficiency

Thrombosis and Haemostasis ◽

10.1055/s-0038-1645677 ◽

1990 ◽

Vol 63 (01) ◽

pp. 013-015 ◽

Cited By ~ 15

Author(s):

E J Johnson ◽

C R M Prentice ◽

L A Parapia

Keyword(s):

Risk Factors ◽

Venous Thromboembolism ◽

Potential Risk ◽

Antithrombin Iii ◽

Arterial Disease ◽

Coagulation System ◽

Early Age ◽

Arterial Thromboembolism ◽

Potential Risk Factors ◽

Antithrombin Iii Deficiency

SummaryAntithrombin III (ATIII) deficiency is one of the few known abnormalities of the coagulation system known to predispose to venous thromboembolism but its relation to arterial disease is not established. We describe two related patients with this disorder, both of whom suffered arterial thrombotic events, at an early age. Both patients had other potential risk factors, though these would normally be considered unlikely to lead to such catastrophic events at such an age. Thrombosis due to ATIII deficiency is potentially preventable, and this diagnosis should be sought more frequently in patients with arterial thromboembolism, particularly if occurring at a young age. In addition, in patients with known ATIII deficiency, other risk factors for arterial disease should be eliminated, if possible. In particular, these patients should be counselled against smoking.

Download Full-text