scholarly journals 1475Effects of climate factors on the dengue fever in Paraguay: generalized additive model in 2014-2020

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Raquel Elizabeth Gomez Gomez
Keyword(s):  
Relative Humidity ◽  
Dengue Fever ◽  
Additive Model ◽  
Climate Factors ◽  
Final Model ◽  
Generalized Additive Modeling ◽  
Increasing Trend ◽  
The Mean ◽  
Additive Modeling ◽  
Dengue Control

Abstract Background Dengue fever is disease transmitted by mostly Aedes spp. This study aims investigate the association between climate factors and dengue incidence in Paraguay, considered as an endemic disease since 2009. Methods We extracted incidence of dengue by week from 2014-2020 national health surveillance, Paraguay. The climate factors, including rainfall, sunshine, minimum temperate, air pressure, relative humidity and wind were extracted from Directorate of Meteorology and Hydrology and aggregated as a weekly data. Generalized additive modeling was performed, adjusted by seasonality and population. Lags between 0-10 weeks were chosen for according to rho statistics of Spearman’s test. Results A total of dengue fever was 40,593 in study period. The mean cumulative incidence per 10,000 populations was 22.37 (standard deviation: 93.27). All six climate factors and seasonality were significant in the final model with the adjusted R-square 18.6%. Rainfall (relative risk [RR]: 0.51), relative humidity (RR: 0.25) and wind (RR: 0.19) showed negative trends with the increase of dengue while atmospheric pressure (RR: 9.32) and sunshine (RR: 0.12) showed positive associations. Minimum temperature showed increasing trend until 15ºC (1ºC increase in 4-fold incidence). The lag of each factor was selected between 2 to 10 weeks. Conclusion Climate factors showed associations with dengue fever in Paraguay. Such climate factors should be considered along with the dengue surveillance in endemic areas for effective dengue control. Key messages Climate factors showed significant dynamic associations with dengue incidence in Paraguay.

scholarly journals Climate Variability, Dengue Vector Abundance and Dengue Fever Cases in Dhaka, Bangladesh: A Time-Series Study

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 905
Author(s):  
Sabrina Islam ◽  
C. Emdad Haque ◽  
Shakhawat Hossain ◽  
John Hanesiak
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Dengue Fever ◽  
Climatic Factors ◽  
Time Lag ◽  
Additive Model ◽  
Climate Change And Variability ◽  
Aedes Mosquitoes ◽  
Vector Abundance ◽  
The Mean

Numerous studies on climate change and variability have revealed that these phenomena have noticeable influence on the epidemiology of dengue fever, and such relationships are complex due to the role of the vector—the Aedes mosquitoes. By undertaking a step-by-step approach, the present study examined the effects of climatic factors on vector abundance and subsequent effects on dengue cases of Dhaka city, Bangladesh. Here, we first analyzed the time-series of Stegomyia indices for Aedes mosquitoes in relation to temperature, rainfall and relative humidity for 2002–2013, and then in relation to reported dengue cases in Dhaka. These data were analyzed at three sequential stages using the generalized linear model (GLM) and generalized additive model (GAM). Results revealed strong evidence that an increase in Aedes abundance is associated with the rise in temperature, relative humidity, and rainfall during the monsoon months, that turns into subsequent increases in dengue incidence. Further we found that (i) the mean rainfall and the lag mean rainfall were significantly related to Container Index, and (ii) the Breteau Index was significantly related to the mean relative humidity and mean rainfall. The relationships of dengue cases with Stegomyia indices and with the mean relative humidity, and the lag mean rainfall were highly significant. In examining longitudinal (2001–2013) data, we found significant evidence of time lag between mean rainfall and dengue cases.

scholarly journals Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis

2020 ◽  
Author(s):  
Zonglin He ◽  
Yiqiao Chin ◽  
Jian Huang ◽  
Yi He ◽  
Babatunde O. Akinwunmi ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Disease Transmission ◽  
Large Scale ◽  
Meteorological Factors ◽  
Pearson Correlation ◽  
Average Temperature ◽  
Generalized Additive Modeling ◽  
Geographical Regions ◽  
Asian Cities ◽  
Additive Modeling

AbstractAIMTo investigate the associations of meteorological factors and the daily new cases of coronavirus disease (COVID-19) in nine Asian cities.METHODPearson’s correlation and generalized additive modeling were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available.RESULTSThe Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=-0.565, P<0.01), Shanghai (r=-0.471, P<0.01), and Guangzhou (r=-0.530, P<0.01), yet in contrast, positively correlated with that in Japan (r=0.441, P<0.01). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), generalized additive modeling analysis showed the number of daily new confirmed cases was positively associated with both average temperature and relative humidity, especially in lagged 3d model, where a positive influence of temperature on the daily new confirmed cases was discerned in 5 cities except in Beijing, Wuhan, Korea, and Malaysia. Nevertheless, the results were inconsistent across cities and lagged time, suggesting meteorological factors were unlikely to greatly influence the COVID-19 epidemic.CONCLUSIONThe associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and lagged time. Large-scale public health measures and expanded regional research are still required until a vaccine becomes available and herd immunity is established.Significance statementWith increasing COVID-19 cases across China and the world, and previous studies showing that meteorological factors may be associated with infectious disease transmission, the saying has it that when summer comes, the epidemic of COVID-19 may simultaneously fade away. We demonstrated the influence of meteorological factors on the daily domestic new cases of coronavirus disease (COVID-19) in nine Asian cities. And we found that the associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and time. We think this important topic may give better clues on prevention, management, and preparation for new events or new changes that could happen in the COVID-19 epidemiology in various geographical regions and as we move towards Summer.

EL NINO RELATED CLIMATE AND DENGUE FEVER CASES IN JEDDAH, SAUDI ARABIA

2019 ◽  
Vol 25 (1) ◽  
Author(s):  
MASROOR ALI KHAN ◽  
KHALID AL GHAMDI ◽  
JAZEM A. MEHYOUB ◽  
RAKHSHAN KHAN
Keyword(s):  
Relative Humidity ◽  
Dengue Fever ◽  
El Niño ◽  
Significant Relationship ◽  
El Nino ◽  
Climate Data ◽  
Light Traps ◽  
Mosquito Abundance ◽  
Dengue Transmission ◽  
The Relationship

The focus of this study is to find the relationship between El Nino and dengue fever cases in the study area.Mosquito density was recorded with the help of light traps and through aspirators collection. Climate data were obtained from National Meteorology and Environment centre. (Year wise El Nino and La Nina data are according to NOAA & Golden Gate Weather Services). Statistical methods were used to establish the correlation coefficient between different factors. A high significant relationship was observed between Relative Humidity and Dengue fever cases, but Aedes abundance had no significant relationship with either Relative humidity and Temperature. Our conclusion is that the El Nino does not affect the dengue transmission and Aedes mosquito abundance in this region, which is supported by earlier works.

scholarly journals Trends and Clinico-Epidemiological Features of Human Rabies Cases in Bangladesh, 2006–2018

2020 ◽  
Vol 41 (S1) ◽  
pp. s416-s416
Author(s):  
Sumon Ghosh ◽  
Md. Sohel Rana ◽  
Sukanta Chowdhury
Keyword(s):  
Effective Means ◽  
Scale Up ◽  
Traditional Healers ◽  
Human Rabies ◽  
Epidemiological Analysis ◽  
Increasing Trend ◽  
The Mean ◽  
Death Cases ◽  
Death Data

Background: Vaccinating dogs against rabies is an effective means of reducing human rabies. Methods: We analyzed 1,327 clinically diagnosed human rabies deaths and mass dog vaccination (MDV) data during 2006–2018 to quantify the impacts of MDV on human rabies incidence in Bangladesh and a subset of rabies death data (n = 422) for clinico-epidemiological analysis. Results: We found a positive and increasing trend of dog population vaccination (P = .01 and τ = 0.71) and a negative and declining trend (P < .001 and τ = −0.88) of human rabies cases (correlation coefficient, −0.82). Among 422 human rabies death cases, most victims (78%) sought treatment from traditional healers, and 12% received postexposure prophylaxis (PEP). The mean incubation period of rabies cases with exposure sites on the head and neck (35 days) was shorter than the upper limb (mean, 64 days; P = .02) and lower limb (mean, 89 days; P < .01). MDV is effective for reducing human rabies cases in Bangladesh. Conclusions: Creating awareness among the animal bite victims to stop relying on traditional healers rather seeking PEP, addressing the role of traditional healers through an awareness education program in respect to the treatment of dog bites, ensuring availability of PEP, and continuing to scale up MDV can help prevent human rabies deaths.Funding: NoneDisclosures: None

scholarly journals From scenario-based seismic hazard to scenario-based landslide hazard: fast-forwarding to the future via statistical simulations

2021 ◽  
Author(s):  
Luigi Lombardo ◽  
Hakan Tanyas
Keyword(s):  
Ground Motion ◽  
Landslide Susceptibility ◽  
Additive Model ◽  
Landslide Hazard ◽  
Northridge Earthquake ◽  
Ground Acceleration ◽  
Temporal Dimension ◽  
Earthquake Scenario ◽  
The Mean ◽  
Ground Motion Scenarios

AbstractGround motion scenarios exists for most of the seismically active areas around the globe. They essentially correspond to shaking level maps at given earthquake return times which are used as reference for the likely areas under threat from future ground displacements. Being landslides in seismically actively regions closely controlled by the ground motion, one would expect that landslide susceptibility maps should change as the ground motion patterns change in space and time. However, so far, statistically-based landslide susceptibility assessments have primarily been used as time-invariant.In other words, the vast majority of the statistical models does not include the temporal effect of the main trigger in future landslide scenarios. In this work, we present an approach aimed at filling this gap, bridging current practices in the seismological community to those in the geomorphological and statistical ones. More specifically, we select an earthquake-induced landslide inventory corresponding to the 1994 Northridge earthquake and build a Bayesian Generalized Additive Model of the binomial family, featuring common morphometric and thematic covariates as well as the Peak Ground Acceleration generated by the Northridge earthquake. Once each model component has been estimated, we have run 1000 simulations for each of the 217 possible ground motion scenarios for the study area. From each batch of 1000 simulations, we have estimated the mean and 95% Credible Interval to represent the mean susceptibility pattern under a specific earthquake scenario, together with its uncertainty level. Because each earthquake scenario has a specific return time, our simulations allow to incorporate the temporal dimension into any susceptibility model, therefore driving the results toward the definition of landslide hazard. Ultimately, we also share our results in vector format – a .mif file that can be easily converted into a common shapefile –. There, we report the mean (and uncertainty) susceptibility of each 1000 simulation batch for each of the 217 scenarios.

Nonlinearities in bilingual visual word recognition: An introduction to generalized additive modeling

2021 ◽  
pp. 1-8
Author(s):  
Koji Miwa ◽  
Harald Baayen
Keyword(s):  
Lexical Decision ◽  
Tensor Product ◽  
Nonlinear Interaction ◽  
Mixed Model ◽  
Nonlinear Effects ◽  
Regression Splines ◽  
Generalized Additive Mixed Model ◽  
Generalized Additive Modeling ◽  
Additive Modeling ◽  
Cross Language

Abstract This paper introduces the generalized additive mixed model (GAMM) and the quantile generalized additive mixed model (QGAMM) through reanalyses of bilinguals’ lexical decision data from Dijkstra et al. (2010) and Miwa et al. (2014). We illustrate how regression splines can be used to test for nonlinear effects of cross-language similarity in form as well as for controlling experimental trial effects. We further illustrate the tensor product smooth for a nonlinear interaction between cross-language semantic similarity and word frequency. Finally, we show how the QGAMM helps clarify whether the effect of a particular predictor is constant across distributions of RTs.

scholarly journals Risk factors of dengue fever in an urban area in Vietnam: a case-control study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Thang Nguyen-Tien ◽  
Duy Cuong Do ◽  
Xuan Luat Le ◽  
Thi Hai Dinh ◽  
Mats Lindeborg ◽  
...  
Keyword(s):  
Risk Factors ◽  
Dengue Fever ◽  
Prevention And Control ◽  
Case Control Study ◽  
Case Control ◽  
Younger Adults ◽  
The Mean ◽  
Dengue Prevention ◽  
And Control ◽  
Control Study

Abstract Background Dengue is a mosquito-borne flavivirus present in many metropolitan cities of tropical countries. Methods During and after the dengue season (September 2018 to January 2019), we conducted a case-control study in order to determine the risk factors for dengue fever in Hanoi city, Vietnam. 98 dengue patients and 99 patients with other acute infections, such as Hepatitis B virus infection, were recruited at Department of Infectious Disease of Bach Mai national hospital in Hanoi. Patients were interviewed using a structured questionnaire covering demographic, housing, environmental factors and knowledge, attitude, and practice on dengue prevention and control. Univariate analysis and multivariable logistic regression were used to determine the risk factors of dengue status. Results The mean score of knowledge items and practice items was only 7.9 out of total 19 points and 3.9 out of total 17 points, respectively. While the mean score of attitude items was 4.8 out of total 6 points. Multivariable logistic regression indicated that older patients had lesser risk of getting dengue infection as compared to younger adults aged 16–30, and patients living in peri-urban districts were less likely to suffer of dengue fever than patients living in central urban districts (OR = 0.31; 95% CI 0.13–0.75). This study could not find any association with occupation, water storage habit, knowledge, attitude, or practice on dengue prevention. Conclusions All patients had a relatively low level of knowledge and practice on dengue prevention and control. However, the attitude of the participants was good. We found that age group and living district were the risk factors correlated with the dengue status. Communication programs on raising dengue awareness should be repeated all year round and target particular groups of adolescents, younger adults, landlords and migrants from other provinces to improve their knowledge and encourage them to implement preventive measures against dengue fever.

scholarly journals Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia

2015 ◽  
Vol 9 (12) ◽  
pp. e0004211 ◽  
Author(s):  
Magali Teurlai ◽  
Christophe Eugène Menkès ◽  
Virgil Cavarero ◽  
Nicolas Degallier ◽  
Elodie Descloux ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Dengue Fever ◽  
New Caledonia ◽  
Climate Factors ◽  
Factors Associated ◽  
Worked Example

Growth performance of Acheta domesticus and Gryllus bimaculatus production reared under improvised cage system for increased returns and food security

2020 ◽  
pp. 1-10
Author(s):  
C.A. Ngonga ◽  
C.O. Gor ◽  
E.A. Okuto ◽  
M.A. Ayieko
Keyword(s):  
Relative Humidity ◽  
Growth Performance ◽  
Additive Model ◽  
Acheta Domesticus ◽  
Cotton Wool ◽  
Conventional System ◽  
Gryllus Bimaculatus ◽  
Generalised Additive Model ◽  
Cage System ◽  
Significant Difference

Cricket farming is emerging as a new venture in Kenya poised to help alleviate protein deficiency and improve household living standards. However, competing, limited and unaffordable rearing systems constrain productivity and optimisation of this new enterprise. This study sought to evaluate the growth performance of Acheta domesticus and Gryllus bimaculatus reared in improvised cage system to assess its technical effectiveness. Twenty-day old of both species of crickets were separately reared in improvised and conventional cage systems for comparison purposes. Whereas an improvised cage system is a set of structure devised using locally available materials especially where the standard materials are limited, a conventional cage system is a set of structure made of standard and ordinary materials. The improvised system comprised of bamboo hideouts, clean scrap blankets for drinking and laying, cut bamboo stem as drinking platter and the plywood-based cages while conventional system comprised of egg carton hideouts, cotton-wool for drinking and laying, plastic petri-dishes, and plastic buckets. Each group of crickets (100 live crickets) was daily provided with equal amount of feed and water. Average weekly temperature and relative humidity profiles were recorded using HOBO data loggers. Further, 49 live crickets per treatment were randomly sampled and weighed weekly. Generalised additive model and analysis of variance were adopted to model the data therefrom using R. The cage system had a significant effect on the growth performance of the crickets. The mean weight of the cricket species differed, but not the interaction with the cage system. Similarly, species, temperature and relative humidity also influenced the growth performance. Compared to the conventional system, improvised cage system showed better results in realising high cricket productivity though there was no significant difference in growth performance between the two systems. The focus therefore should be to evaluate the egg productivity in scrap blanket in relation to cotton wool and cost effectiveness in improvised system to inform future farm decisions.

scholarly journals Temporal Variations and Associated Remotely Sensed Environmental Variables of Dengue Fever in Chitwan District, Nepal

2018 ◽  
Vol 7 (7) ◽  
pp. 275 ◽  
Author(s):  
Bipin Acharya ◽  
Chunxiang Cao ◽  
Min Xu ◽  
Laxman Khanal ◽  
Shahid Naeem ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Dengue Fever ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Environmental Variables ◽  
Vegetation Index ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Remotely Sensed ◽  
Cross Correlation Analysis

Dengue fever is one of the leading public health problems of tropical and subtropical countries across the world. Transmission dynamics of dengue fever is largely affected by meteorological and environmental factors, and its temporal pattern generally peaks in hot-wet periods of the year. Despite this continuously growing problem, the temporal dynamics of dengue fever and associated potential environmental risk factors are not documented in Nepal. The aim of this study was to fill this research gap by utilizing epidemiological and earth observation data in Chitwan district, one of the frequent dengue outbreak areas of Nepal. We used laboratory confirmed monthly dengue cases as a dependent variable and a set of remotely sensed meteorological and environmental variables as explanatory factors to describe their temporal relationship. Descriptive statistics, cross correlation analysis, and the Poisson generalized additive model were used for this purpose. Results revealed that dengue fever is significantly associated with satellite estimated precipitation, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) synchronously and with different lag periods. However, the associations were weak and insignificant with immediate daytime land surface temperature (dLST) and nighttime land surface temperature (nLST), but were significant after 4–5 months. Conclusively, the selected Poisson generalized additive model based on the precipitation, dLST, and NDVI explained the largest variation in monthly distribution of dengue fever with minimum Akaike’s Information Criterion (AIC) and maximum R-squared. The best fit model further significantly improved after including delayed effects in the model. The predicted cases were reasonably accurate based on the comparison of 10-fold cross validation and observed cases. The lagged association found in this study could be useful for the development of remote sensing-based early warning forecasts of dengue fever.

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