scholarly journals Effect of climate factors on Hand-Foot-Mouth Disease: A generalized additive model approach

2021 ◽  
Vol 1988 (1) ◽  
pp. 012102
Author(s):  
N A A Wahid ◽  
J Suhaila ◽  
H A Rahman ◽  
A Sulekan
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tao Fu ◽  
Ting Chen ◽  
Zhen-Bin Dong ◽  
Shu-Ying Luo ◽  
Ziping Miao ◽  
...  

Abstract Hand-foot-mouth disease (HFMD) is an acute intestinal virus infectious disease which is one of major public health problems in mainland China. Previous studies indicated that HFMD was significantly influenced by climatic factors, but the associated factors were different in different areas and few study on HFMD forecast models was conducted. Here, we analyzed epidemiological characteristics of HFMD in Yiwu City, Zhejiang Province and constructed three forecast models. Overall, a total of 32554 HFMD cases were reported and 12 cases deceased in Yiwu City, Zhejiang Province. The incidence of HFMD peaked every other year and the curve of HFMD incidence had an approximately W-shape. The majority of HFMD cases were children and 95.76% cases aged ≤5 years old from 2008 to 2016. Furthermore, we constructed and compared three forecast models using autoregressive integrated moving average (ARIMA) model, negative binomial regression model (NBM), and quasi-Poisson generalized additive model (GAM). All the three models had high agreements between predicted values and observed values, while GAM fitted best. The exposure-response curve of monthly mean temperature and HFMD was approximately V-shaped. Our study explored epidemiological characteristics of HFMD in Yiwu City and provided accurate methods for early warning which would be great importance for the control and prevention of HFMD.


2020 ◽  
Vol 16 (2) ◽  
pp. 230-240
Author(s):  
L Handayani ◽  
R Amelia ◽  
F H A Putera

Climate models that are able to simulate rainfall in Indonesia so far have not been found. The highly complex topography and interaction of the sea, land and atmosphere adds to the complexity of simulations and predictions of rainfall in Indonesia, particularly in Central Sulawesi. This research focuses on utilizing the results of prediction or forecast rainfall. Rainfall forecasting results obtained are then modeled with data on the level of rice production, so we can predict the future supply of rice (rice). This study examines statistical downscaling modeling with a generalized additive model approach to describe the rainfall events that occur within a certain time period. The data used is rainfall data in Central Sulawesi Province, because this region is a supplier of rice in Sulawesi.


2021 ◽  
Vol 9 (5) ◽  
pp. 324-331
Author(s):  
Nurmarni Athirah Abdul Wahid ◽  
Jamaludin Suhaila ◽  
Haliza Abd. Rahman

Author(s):  
Elisabetta Venturini ◽  
Luisa Galli ◽  
Elena Chiappini ◽  
Maurizio De Martino ◽  
Andrea Bassi

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