scholarly journals The impact of climate suitability, urbanisation, and connectivity on the expansion of dengue in 21st century Brazil

2021 ◽  
Vol 15 (12) ◽  
pp. e0009773
Author(s):  
Sophie A. Lee ◽  
Theodoros Economou ◽  
Rafael de Castro Catão ◽  
Christovam Barcellos ◽  
Rachel Lowe
Keyword(s):  
Control Strategies ◽  
Additive Model ◽  
Northern Coast ◽  
Urban Network ◽  
Dengue Transmission ◽  
Transmission Zone ◽  
Dengue Outbreaks ◽  
The Impact ◽  
Temperature Suitability ◽  
South Brazil

Dengue is hyperendemic in Brazil, with outbreaks affecting all regions. Previous studies identified geographical barriers to dengue transmission in Brazil, beyond which certain areas, such as South Brazil and the Amazon rainforest, were relatively protected from outbreaks. Recent data shows these barriers are being eroded. In this study, we explore the drivers of this expansion and identify the current limits to the dengue transmission zone. We used a spatio-temporal additive model to explore the associations between dengue outbreaks and temperature suitability, urbanisation, and connectivity to the Brazilian urban network. The model was applied to a binary outbreak indicator, assuming the official threshold value of 300 cases per 100,000 residents, for Brazil’s municipalities between 2001 and 2020. We found a nonlinear relationship between higher levels of connectivity to the Brazilian urban network and the odds of an outbreak, with lower odds in metropoles compared to regional capitals. The number of months per year with suitable temperature conditions for Aedes mosquitoes was positively associated with the dengue outbreak occurrence. Temperature suitability explained most interannual and spatial variation in South Brazil, confirming this geographical barrier is influenced by lower seasonal temperatures. Municipalities that had experienced an outbreak previously had double the odds of subsequent outbreaks. We identified geographical barriers to dengue transmission in South Brazil, western Amazon, and along the northern coast of Brazil. Although a southern barrier still exists, it has shifted south, and the Amazon no longer has a clear boundary. Few areas of Brazil remain protected from dengue outbreaks. Communities living on the edge of previous barriers are particularly susceptible to future outbreaks as they lack immunity. Control strategies should target regions at risk of future outbreaks as well as those currently within the dengue transmission zone.

scholarly journals The impact of climate suitability, urbanisation, and connectivity on the expansion of dengue in 21st century Brazil

2021 ◽  
Author(s):  
Sophie Lee ◽  
Theo Economou ◽  
Rafael de Castro Catão ◽  
Christovam Barcellos ◽  
Rachel Lowe
Keyword(s):  
Control Strategies ◽  
Additive Model ◽  
Northern Coast ◽  
Urban Network ◽  
Dengue Transmission ◽  
Transmission Zone ◽  
Dengue Outbreaks ◽  
The Impact ◽  
Temperature Suitability ◽  
South Brazil

Dengue is hyperendemic in Brazil, with outbreaks affecting all regions. Previous studies identified geographical barriers to dengue transmission in Brazil, beyond which certain areas, such as South Brazil and the Amazon rainforest, were relatively protected from outbreaks. Recent data shows these barriers are being eroded. In this study, we explore the drivers of this expansion and identify the current limits to the dengue transmission zone. We used a spatio-temporal additive model to explore the associations between dengue outbreaks and temperature suitability, urbanisation, and connectivity to the Brazilian urban network. The model was applied to a binary outbreak indicator, assuming the official threshold value of 300 cases per 100,000 residents, for Brazil's municipalities between 2001 and 2020. We found a nonlinear relationship between higher levels of connectivity to the Brazilian urban network and the odds of an outbreak, with lower odds in metropoles compared to regional capitals. The number of months per year with suitable temperature conditions for Aedes mosquitoes was positively associated with the dengue outbreak occurrence. Temperature suitability explained most interannual and spatial variation in South Brazil, confirming this geographical barrier is influenced by lower seasonal temperatures. Municipalities that had experienced an outbreak previously had double the odds of subsequent outbreaks, indicating that dengue tends to become established in areas after introduction. We identified geographical barriers to dengue transmission in South Brazil, western Amazon, and along the northern coast of Brazil. Although a southern barrier still exists, it has shifted south, and the Amazon no longer has a clear boundary. Few areas of Brazil remain protected from dengue outbreaks. Communities living on the edge of previous barriers are particularly susceptible to future outbreaks as they lack immunity. Control strategies should target regions at risk of future outbreaks as well as those currently within the dengue transmission zone.

scholarly journals Predicting dengue outbreaks at neighbourhood level using human mobility in urban areas

2020 ◽  
Vol 17 (171) ◽  
pp. 20200691
Author(s):  
Rafael Bomfim ◽  
Sen Pei ◽  
Jeffrey Shaman ◽  
Teresa Yamana ◽  
Hernán A. Makse ◽  
...  
Keyword(s):  
Neural Networks ◽  
Dengue Virus ◽  
Urban Areas ◽  
Human Mobility ◽  
Mechanistic Models ◽  
Mobility Data ◽  
Dengue Transmission ◽  
Neighbourhood Level ◽  
Dengue Outbreaks ◽  
The Impact

Dengue is a vector-borne disease transmitted by the Aedes genus mosquito. It causes financial burdens on public health systems and considerable morbidity and mortality. Tropical regions in the Americas and Asia are the areas most affected by the virus. Fortaleza is a city with approximately 2.6 million inhabitants in northeastern Brazil that, during the recent decades, has been suffering from endemic dengue transmission, interspersed with larger epidemics. The objective of this paper is to study the impact of human mobility in urban areas on the spread of the dengue virus, and to test whether human mobility data can be used to improve predictions of dengue virus transmission at the neighbourhood level. We present two distinct forecasting systems for dengue transmission in Fortaleza: the first using artificial neural network methods and the second developed using a mechanistic model of disease transmission. We then present enhanced versions of the two forecasting systems that incorporate bus transportation data cataloguing movement among 119 neighbourhoods in Fortaleza. Each forecasting system was used to perform retrospective forecasts for historical dengue outbreaks from 2007 to 2015. Results show that both artificial neural networks and mechanistic models can accurately forecast dengue cases, and that the inclusion of human mobility data substantially improves the performance of both forecasting systems. While the mechanistic models perform better in capturing seasons with large-scale outbreaks, the neural networks more accurately forecast outbreak peak timing, peak intensity and annual dengue time series. These results have two practical implications: they support the creation of public policies from the use of the models created here to combat the disease and help to understand the impact of urban mobility on the epidemic in large cities.

scholarly journals Geo-Epidemiology of Malaria at the Health Area Level, Dire Health District, Mali, 2013–2017

2020 ◽  
Vol 17 (11) ◽  
pp. 3982 ◽  
Author(s):  
Mady Cissoko ◽  
Issaka Sagara ◽  
Moussa H. Sankaré ◽  
Sokhna Dieng ◽  
Abdoulaye Guindo ◽  
...  
Keyword(s):  
Multiple Correspondence Analysis ◽  
Malaria Incidence ◽  
Control Strategies ◽  
Additive Model ◽  
Principal Component ◽  
Health District ◽  
World Health ◽  
High Transmission ◽  
Synthetic Indicators ◽  
The Impact

Background: According to the World Health Organization, there were more than 228 million cases of malaria globally in 2018, with 93% of cases occurring in Africa; in Mali, a 13% increase in the number of cases was observed between 2015 and 2018; this study aimed to evaluate the impact of meteorological and environmental factors on the geo-epidemiology of malaria in the health district of Dire, Mali. Methods: Meteorological and environmental variables were synthesized using principal component analysis and multiple correspondence analysis, the relationship between malaria incidence and synthetic indicators was determined using a multivariate general additive model; hotspots were detected by SaTScan. Results: Malaria incidence showed high inter and intra-annual variability; the period of high transmission lasted from September to February; health areas characterized by proximity to the river, propensity for flooding and high agricultural yield were the most at risk, with an incidence rate ratio of 2.21 with confidence intervals (95% CI: 1.85–2.58); malaria incidence in Dire declined from 120 to 20 cases per 10,000 person-weeks between 2013 and 2017. Conclusion: The identification of areas and periods of high transmission can help improve malaria control strategies.

scholarly journals Interaction of climate and socio-ecological environment drives the dengue outbreak in epidemic region of China

2021 ◽  
Vol 15 (10) ◽  
pp. e0009761
Author(s):  
Chenlu Li ◽  
Xiaoxu Wu ◽  
Scott Sheridan ◽  
Jay Lee ◽  
Xiaofeng Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Interactive Effect ◽  
Ecological Factors ◽  
Single Factor ◽  
Multiple Factors ◽  
Dengue Transmission ◽  
The Future ◽  
Dengue Outbreaks ◽  
Long Time ◽  
The Impact

Transmission of dengue virus is a complex process with interactions between virus, mosquitoes and humans, influenced by multiple factors simultaneously. Studies have examined the impact of climate or socio-ecological factors on dengue, or only analyzed the individual effects of each single factor on dengue transmission. However, little research has addressed the interactive effects by multiple factors on dengue incidence. This study uses the geographical detector method to investigate the interactive effect of climate and socio-ecological factors on dengue incidence from two perspectives: over a long-time series and during outbreak periods; and surmised on the possibility of dengue outbreaks in the future. Results suggest that the temperature plays a dominant role in the long-time series of dengue transmission, while socio-ecological factors have great explanatory power for dengue outbreaks. The interactive effect of any two factors is greater than the impact of single factor on dengue transmission, and the interactions of pairs of climate and socio-ecological factors have more significant impact on dengue. Increasing temperature and surge in travel could cause dengue outbreaks in the future. Based on these results, three recommendations are offered regarding the prevention of dengue outbreaks: mitigating the urban heat island effect, adjusting the time and frequency of vector control intervention, and providing targeted health education to travelers at the border points. This study hopes to provide meaningful clues and a scientific basis for policymakers regarding effective interventions against dengue transmission, even during outbreaks.

scholarly journals Development of a mechanistic dengue simulation model for Guangzhou

2019 ◽  
Vol 147 ◽  
Author(s):  
G. Mincham ◽  
K. L. Baldock ◽  
H. Rozilawati ◽  
C. R. Williams
Keyword(s):  
Simulation Model ◽  
Control Strategies ◽  
Dengue Infection ◽  
Management Strategies ◽  
Surveillance Data ◽  
Effective Vaccine ◽  
Dengue Transmission ◽  
Dengue Outbreaks ◽  
Computer Based ◽  
The City

AbstractDengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.

scholarly journals Power Hardware-in-the-Loop-Based Performance Analysis of Different Converter Controllers for Fast Active Power Regulation in Low-Inertia Power Systems

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3274
Author(s):  
Jose Rueda Torres ◽  
Zameer Ahmad ◽  
Nidarshan Veera Kumar ◽  
Elyas Rakhshani ◽  
Ebrahim Adabi ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Power Systems ◽  
Real Time ◽  
Control Strategies ◽  
Active Power ◽  
Power Electronic ◽  
Hardware In The Loop ◽  
Digital Controllers ◽  
Power Regulation ◽  
The Impact

Future electrical power systems will be dominated by power electronic converters, which are deployed for the integration of renewable power plants, responsive demand, and different types of storage systems. The stability of such systems will strongly depend on the control strategies attached to the converters. In this context, laboratory-scale setups are becoming the key tools for prototyping and evaluating the performance and robustness of different converter technologies and control strategies. The performance evaluation of control strategies for dynamic frequency support using fast active power regulation (FAPR) requires the urgent development of a suitable power hardware-in-the-loop (PHIL) setup. In this paper, the most prominent emerging types of FAPR are selected and studied: droop-based FAPR, droop derivative-based FAPR, and virtual synchronous power (VSP)-based FAPR. A novel setup for PHIL-based performance evaluation of these strategies is proposed. The setup combines the advanced modeling and simulation functions of a real-time digital simulation platform (RTDS), an external programmable unit to implement the studied FAPR control strategies as digital controllers, and actual hardware. The hardware setup consists of a grid emulator to recreate the dynamic response as seen from the interface bus of the grid side converter of a power electronic-interfaced device (e.g., type-IV wind turbines), and a mockup voltage source converter (VSC, i.e., a device under test (DUT)). The DUT is virtually interfaced to one high-voltage bus of the electromagnetic transient (EMT) representation of a variant of the IEEE 9 bus test system, which has been modified to consider an operating condition with 52% of the total supply provided by wind power generation. The selected and programmed FAPR strategies are applied to the DUT, with the ultimate goal of ascertaining its feasibility and effectiveness with respect to the pure software-based EMT representation performed in real time. Particularly, the time-varying response of the active power injection by each FAPR control strategy and the impact on the instantaneous frequency excursions occurring in the frequency containment periods are analyzed. The performed tests show the degree of improvements on both the rate-of-change-of-frequency (RoCoF) and the maximum frequency excursion (e.g., nadir).

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

scholarly journals Prevalence of mastitis in Nigerian livestock: a Review

2020 ◽  
Vol 1 (1) ◽  
pp. 20-29
Author(s):  
Hussaini Ojagefu Adamu ◽  
Rahimat Oshuwa Hussaini ◽  
Cedric Obasuyi ◽  
Linus Irefo Anagha ◽  
Gabriel Oscy Okoduwa
Keyword(s):  
Control Strategies ◽  
Dairy Farms ◽  
Livestock Production ◽  
Sub Saharan Africa ◽  
Economic Losses ◽  
Ecological Development ◽  
Management Plans ◽  
Sub Saharan ◽  
Control And Management ◽  
The Impact

AbstractMastitis is a disease of livestock that directly impede livestock production and thus hindering the socio-ecological development of sub-Saharan Africa. Studies have estimated the prevalence of this disease in 30% of Africa countries, with Ethiopia having the highest prevalence. The coverage is low, despite the wide livestock and dairy farms distribution in Africa. Furthermore, estimated economic losses due to the impact of mastitis are lacking in Nigeria. The disease is endemic in Nigeria as indicated by the available data and there are no proposed management plans or control strategies. This review is thus presented to serve as a wakeup call to all parties involved to intensify efforts towards the diagnosis, control, and management of the disease in Nigeria.

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