scholarly journals Geospatial Analysis of Covid-19 to Respond to Pandemic Outbreaks: A Case Study in Bangkok Metropolitan Region, Thailand

2021 ◽  
pp. 68-80
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Spatial Epidemiology ◽  
Control Strategies ◽  
Distribution Patterns ◽  
Metropolitan Region ◽  
Spatial Spread ◽  
Vector Borne Diseases ◽  
Related Data ◽  
Healthcare Settings

Coronavirus (Covid-19) has to date (March 29th 2020) infected over 81,000 Chinese citizens, mostly in Hubei Province, since it was first identified in December 2019. It has so far spread to more than 202 countries. On the 31th of March 2020, the total number of laboratory-confirmed COVID-19 cases reported by Ministry of Public Health (MoPH) in Thailand is 1524, of which 127 have recovered, 1388 are receiving treatment (17 cases are severe) in healthcare settings and nine have died. Recently Geographic Information System (GIS) provide epidemiologists and public health officers in the surveillance, monitoring and controlling of many infected diseases such as vector-borne diseases or human-to-human transmission diseases in many countries. Particularly it can provide the functions of collecting, updating and managing disease surveillance and related data, such as geographical factor and socio-economic. They are also pertinent to suit the needs of understanding the spatial spread or diffusion of disease outbreak and response for designing the prevention and control strategies. The major objective of this research is to apply the spatial epidemiology approaches for studying COVID-19 patterns and hotspots in Bangkok Metropolitan Region (BMR), Thailand. The specific objectives are to analyze the COVID-19 patterns in the terms of population and geographic distribution patterns; to detect the COVID-19 incidence rate under different months by using the spatial analysis. This research provides maps to view the pandemic situation of BMR and the provincial level of COVID-19 in particular heat maps and ring maps.

scholarly journals Notifiable diseases after implementation of COVID-19 public health prevention measures in Central Queensland, Australia

2021 ◽  
Vol 45 ◽  
Author(s):  
Odewumi Adegbija ◽  
Jacina Walker ◽  
Nicholas Smoll ◽  
Arifuzzaman Khan ◽  
Julieanne Graham ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
Prevention Measures ◽  
Vector Borne Diseases ◽  
Vaccine Preventable Diseases ◽  
Notifiable Diseases ◽  
Health Measures ◽  
Travel Restrictions

The implementation of public health measures to control the current COVID-19 pandemic (such as wider lockdowns, overseas travel restrictions and physical distancing) is likely to have affected the spread of other notifiable diseases. This is a descriptive report of communicable disease surveillance in Central Queensland (CQ) for six months (1 April to 30 September 2020) after the introduction of physical distancing and wider lockdown measures in Queensland. The counts of notifiable communicable diseases in CQ in the six months were observed and compared with the average for the same months during the years 2015 to 2019. During the study’s six months, there were notable decreases in notifications of most vaccine-preventable diseases such as influenza, pertussis and rotavirus. Conversely, notifications increased for disease groups such as blood-borne viruses, sexually transmitted infections and vector-borne diseases. There were no reported notifications for dengue fever and malaria which are mostly overseas acquired. The notifications of some communicable diseases in CQ were variably affected and the changes correlated with the implementation of the COVID-19 public health measures.

Will integrated surveillance systems for vectors and vector-borne diseases be the future of controlling vector-borne diseases? A practical example from China

2016 ◽  
Vol 144 (9) ◽  
pp. 1895-1903 ◽  
Author(s):  
Y. WU ◽  
F. LING ◽  
J. HOU ◽  
S. GUO ◽  
J. WANG ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Monitoring Systems ◽  
Disease Monitoring ◽  
Surveillance Systems ◽  
Control Vector ◽  
Notifiable Disease ◽  
Vector Borne Diseases ◽  
Vector Borne

SUMMARYVector-borne diseases are one of the world's major public health threats and annually responsible for 30–50% of deaths reported to the national notifiable disease system in China. To control vector-borne diseases, a unified, effective and economic surveillance system is urgently needed; all of the current surveillance systems in China waste resources and/or information. Here, we review some current surveillance systems and present a concept for an integrated surveillance system combining existing vector and vector-borne disease monitoring systems. The integrated surveillance system has been tested in pilot programmes in China and led to a 21·6% cost saving in rodent-borne disease surveillance. We share some experiences gained from these programmes.

scholarly journals Infectious Disease Forecasting for Public Health

2020 ◽  
pp. 45-68
Author(s):  
Stephen A. Lauer ◽  
Alexandria C. Brown ◽  
Nicholas G. Reich
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Disease Surveillance ◽  
Mechanistic Model ◽  
Disease Incidence ◽  
Surveillance Systems ◽  
Vector Borne Diseases ◽  
Common Infectious Disease ◽  
The Face ◽  
Underlying Processes

Forecasting transmission of infectious diseases, especially for vector-borne diseases, poses unique challenges for researchers. Behaviors of and interactions between viruses, vectors, hosts, and the environment each play a part in determining the transmission of a disease. Public health surveillance systems and other sources provide valuable data that can be used to accurately forecast disease incidence. However, many aspects of common infectious disease surveillance data are imperfect: cases may be reported with a delay or in some cases not at all, data on vectors may not be available, and case data may not be available at high geographical or temporal resolution. In the face of these challenges, researchers must make assumptions to either account for these underlying processes in a mechanistic model or to justify their exclusion altogether in a statistical model.

The Ethics of AI in Biomedical Research, Patient Care, and Public Health

2020 ◽  
pp. 702-718 ◽  
Author(s):  
Alessandro Blasimme ◽  
Effy Vayena
Keyword(s):  
Public Health ◽  
Patient Care ◽  
Biomedical Research ◽  
Disease Surveillance ◽  
Ethical Issues ◽  
Ethical Review ◽  
Ethical Challenges ◽  
Healthcare Provision ◽  
Social Scientists ◽  
Ethical Frameworks

This chapter explores ethical issues raised by the use of artificial intelligence (AI) in the domain of biomedical research, healthcare provision, and public health. The litany of ethical challenges that AI in medicine raises cannot be addressed sufficiently by current regulatory and ethical frameworks. The chapter then advances the systemic oversight approach as a governance blueprint, which is based on six principles offering guidance as to the desirable features of oversight structures and processes in the domain of data-intense biomedicine: adaptivity, flexibility, inclusiveness, reflexivity, responsiveness, and monitoring (AFIRRM). In the research domain, ethical review committees will have to incorporate reflexive assessment of the scientific and social merits of AI-driven research and, as a consequence, will have to open their ranks to new professional figures such as social scientists. In the domain of patient care, clinical validation is a crucial issue. Hospitals could equip themselves with “clinical AI oversight bodies” charged with the task of advising clinical administrators. Meanwhile, in the public health sphere, the new level of granularity enabled by AI in disease surveillance or health promotion will have to be negotiated at the level of targeted communities.

scholarly journals An update on the distribution of Glossina (tsetse flies) at the wildlife-human-livestock interface of Akagera National Park, Rwanda

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Richard S. Gashururu ◽  
Samuel M. Githigia ◽  
Methode N. Gasana ◽  
Richard Habimana ◽  
Ndichu Maingi ◽  
...  
Keyword(s):  
National Park ◽  
Control Strategies ◽  
Glossina Pallidipes ◽  
Distribution Patterns ◽  
Tsetse Flies ◽  
Wet Season ◽  
Chi Square ◽  
Large Numbers ◽  
Surrounding Areas ◽  
Biconical Traps

Abstract Background Glossina (tsetse flies) biologically transmit trypanosomes that infect both humans and animals. Knowledge of their distribution patterns is a key element to better understand the transmission dynamics of trypanosomosis. Tsetse distribution in Rwanda has not been well enough documented, and little is known on their current distribution. This study determined the current spatial distribution, abundance, diversity, and seasonal variations of tsetse flies in and around the Akagera National Park. Methods A longitudinal stratified sampling following the seasons was used. Biconical traps were deployed in 55 sites for 6 consecutive days of each study month from May 2018 to June 2019 and emptied every 48 h. Flies were identified using FAO keys, and the number of flies per trap day (FTD) was used to determine the apparent density. Pearson chi-square (χ2) and parametrical tests (t-test and ANOVA) were used to determine the variations between the variables. The significance (p < 0.05) at 95% confidence interval was considered. Logistic regression was used to determine the association between tsetse occurrence and the associated predictors. Results A total of 39,516 tsetse flies were collected, of which 73.4 and 26.6% were from inside Akagera NP and the interface area, respectively. Female flies accounted for 61.3 while 38.7% were males. Two species were identified, i.e. G. pallidipes [n = 29,121, 7.4 flies/trap/day (FTD)] and G. morsitans centralis (n = 10,395; 2.6 FTD). The statistical difference in numbers was significant between the two species (p = 0.000). The flies were more abundant during the wet season (15.8 FTD) than the dry season (4.2 FTD). Large numbers of flies were trapped around the swamp areas (69.1 FTD) inside the park and in Nyagatare District (11.2 FTD) at the interface. Glossina morsitans was 0.218 times less likely to occur outside the park. The chance of co-existing between the two species reduced outside the protected area (0.021 times). Conclusions The occurrence of Glossina seems to be limited to the protected Akagera NP and a narrow band of its surrounding areas. This finding will be crucial to design appropriate control strategies. Glossina pallidipes was found in higher numbers and therefore is conceivably the most important vector of trypanosomosis. Regional coordinated control and regular monitoring of Glossina distribution are recommended. Graphic Abstract

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

scholarly journals Dynamic quarantine: a comparative analysis of the Chilean public health response to COVID-19

2020 ◽  
Vol 148 ◽  
Author(s):  
Gonzalo Grebe ◽  
Javier A. Vélez ◽  
Anton Tiutiunnyk ◽  
Diego Aragón-Caqueo ◽  
Javier Fernández-Salinas ◽  
...  
Keyword(s):  
Public Health ◽  
Comparative Analysis ◽  
Transmission Rate ◽  
National Level ◽  
Metropolitan Region ◽  
Public Health Response ◽  
Country Level ◽  
Health Response ◽  
Primary Vector

Abstract In this study, an analysis of the Chilean public health response to mitigate the spread of COVID-19 is presented. The analysis is based on the daily transmission rate (DTR). The Chilean response has been based on dynamic quarantines, which are established, lifted or prolonged based on the percentage of infected individuals in the fundamental administrative sections, called communes. This analysis is performed at a national level, at the level of the Metropolitan Region (MR) and at the commune level in the MR according to whether the commune did or did not enter quarantine between late March and mid-May of 2020. The analysis shows a certain degree of efficacy in controlling the pandemic using the dynamic quarantine strategy. However, it also shows that apparent control has only been partially achieved to date. With this policy, the control of the DTR partially falls to 4%, where it settles, and the MR is the primary vector of infection at the country level. For this reason, we can conclude that the MR has not managed to control the disease, with variable results within its own territory.

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