scholarly journals Assessing the Effect of Climate Variables on the Incidence of Dengue Cases in the Metropolitan Region of Panama City

2021 ◽  
Vol 18 (22) ◽  
pp. 12108
Author(s):  
Vicente Navarro Navarro Valencia ◽  
Yamilka Díaz ◽  
Juan Miguel Pascale ◽  
Maciej F. Boni ◽  
Javier E. Sanchez-Galan
Keyword(s):  
Neural Network ◽  
Relative Humidity ◽  
Regression Models ◽  
Predictive Performance ◽  
Climatic Variables ◽  
Metropolitan Region ◽  
Climate Variables ◽  
Alert System ◽  
Panama City

The present analysis uses the data of confirmed incidence of dengue cases in the metropolitan region of Panama from 1999 to 2017 and climatic variables (air temperature, precipitation, and relative humidity) during the same period to determine if there exists a correlation between these variables. In addition, we compare the predictive performance of two regression models (SARIMA, SARIMAX) and a recurrent neural network model (RNN-LSTM) on the dengue incidence series. For this data from 1999–2014 was used for training and the three subsequent years of incidence 2015–2017 were used for prediction. The results show a correlation coefficient between the climatic variables and the incidence of dengue were low but statistical significant. The RMSE and MAPE obtained for the SARIMAX and RNN-LSTM models were 25.76, 108.44 and 26.16, 59.68, which suggest that any of these models can be used to predict new outbreaks. Although, it can be said that there is a limited role of climatic variables in the outputs the models. The value of this work is that it helps understand the behaviour of cases in a tropical setting as is the Metropolitan Region of Panama City, and provides the basis needed for a much needed early alert system for the region.

Assessing the Role of Opportunity and Low Self-Control in Juvenile Hacking

2020 ◽  
pp. 001112872097873
Author(s):  
Thomas J. Holt ◽  
Jesse Cale ◽  
Russell Brewer ◽  
Andrew Goldsmith
Keyword(s):  
Regression Models ◽  
Binary Logistic Regression ◽  
Self Control ◽  
Metropolitan Region ◽  
General Theory Of Crime ◽  
Logistic Regression Models ◽  
Computer Hacking ◽  
Theory Of Crime ◽  
Low Self Control

Gottfredson and Hirschi’s general theory of crime argues individuals with low self-control are more likely to engage in crime on and off-line. There is less research considering the role of opportunity, as low self-control should increase individuals’ willingness to act on opportunities to offend. The importance of opportunity is distinct for cybercrime, as technology access may be differentially impacted by various demographic factors. This study surveyed 1,411 South Australian adolescents enrolled at secondary schools across a large metropolitan region to examine the relationships between opportunity and self-control for four forms of computer hacking. A series of binary logistic regression models illustrated that distinct opportunity factors and low self-control are associated with each form of hacking.

scholarly journals A field-based modeling study on ecological characterization of hourly host-seeking behavior and its associated climatic variables in Aedes albopictus

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Qingqing Yin ◽  
Li Li ◽  
Xiang Guo ◽  
Rangke Wu ◽  
Benyun Shi ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Aedes Albopictus ◽  
Regression Models ◽  
Negative Binomial ◽  
Control Measures ◽  
Climatic Variables ◽  
Host Seeking ◽  
Seeking Behavior ◽  
Modeling Study

Abstract Background The global spread of mosquito-borne diseases (MBD) has presented increasing challenges to public health. The transmission of MBD is mainly attributable to the biting behaviors of female mosquitoes. However, the ecological pattern of hourly host-seeking behavior in Aedes albopictus and its association with climatic variables are still not well understood, especially for a precise requirement for establishing an effective risk prediction system of MBD transmission. Methods Mosquito samples and data on mosquito hourly density and site-specific climatic variables, including temperature, relative humidity, illuminance and wind speed, were collected simultaneously in urban outdoor environments in Guangzhou during 2016–2018. Kernel regression models were used to assess the temporal patterns of hourly host-seeking behavior in mosquito populations, and negative binomial regression models in the Bayesian framework were used to investigate the associations of host-seeking behavior with climatic variables. Results Aedes albopictus was abundant, constituting 82% (5569/6790) of the total collected mosquitoes. Host-seeking behavior in Ae. albopictus varied across time and was significantly influenced by climatic variables. The predicted hourly mosquito densities showed non-linear relationships with temperature and illuminance, whereas density increased with relative humidity but generally decreased with wind speed. The range of temperature estimates for female biting was 16.4–37.1 °C, peaking at 26.5 °C (95% credible interval: 25.3–28.1). During the favorable periods, biting behavior of female Ae. albopictus was estimated to occur frequently all day long, presenting a bimodal distribution with peaks within 2–3 h around both dawn and dusk (05:00–08:00 h and 16:00–19:00 h). Moreover, a short-term association in hourly density between the females and males was found. Conclusions Our field-based modeling study reveals that hourly host-seeking behavior of Ae. albopictus exhibits a complex pattern, with hourly variation constrained significantly by climatic variables. These findings lay a foundation for improving MBD risk assessments as well as practical strategies for vector control. For instances of all-day-long frequent female biting during the favorable periods in Guangzhou, effective integrated mosquito control measures must be taken throughout the day and night.

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