scholarly journals Study the Effects of COVID-19 in Punjab, Pakistan using Space-time Scan Statistic for Policy Measures in Regional Agriculture and Food Supply Chain

2021 ◽  
Author(s):  
Sajjad Hussain ◽  
Muhammad Mubeen ◽  
Ashfaq Ahmad ◽  
Shah Fahad ◽  
Wajid Nasim ◽  
...  
Keyword(s):  
Supply Chain ◽  
Food Security ◽  
Food Policy ◽  
Supply And Demand ◽  
Food Service ◽  
Adaptation Strategy ◽  
Space Time ◽  
Scan Statistic ◽  
Agriculture And Food ◽  
Time Scan

Abstract Food service and retailing sectors play a vital role in economics of Punjab, Pakistan. Pakistan is included in top 50 countries which are estimated to face serious agriculture and food deficiency related challenges due to the world-wide pandemic coronavirus 2019 (COVID-19). The aim of this study was to study the effects of COVID-19 on food security and agriculture in Punjab, Pakistan using space-time scan statistic (STSS). A survey was conducted at 720 points in different districts of the province. The STSS detected “active” and emerging clusters that are current at the end of our study aera – particularly 17 clusters were formed while adding the updated case data. ArcGIS 10.3 software was used to find relative risk (RR) values; the maximum RR value was found to be 42.19 and maximum observed cases 53265 during June 15th – July 1st. Due to the highest number of cases of COVID-19 and RR vales during July, mostly farmers faced many difficulties during the cultivation of cotton and rice. Mostly farmers (72%) observed increase in prices of inputs (fertilizers and pesticides) during lockdown. The timely results (attained through STSS and RR) can inform decision makers and public health officials about where to improve the allocation of resources (including those for farming community), also, where to apply stricter quarantines and travel bans. If the supply chain of agriculture related inputs is disturbed, farmers may find it quite difficult to access markets, which could result in a decline in production and sales of crops and livestock in study area. It is suggested that to protection of food security and to decrease the effect of the lockdown, Punjab government needs to review food policy as well as analyze how market forces will respond to the imbalanced storage facilities and capacity, supply and demand, and price control of products. The findings of this study can also help policy-makers to formulate an effective food security and agriculture adaptation strategy.

scholarly journals Space–Time Clustering Characteristics of Malaria in Bhutan at the End Stages of Elimination

2021 ◽  
Vol 18 (11) ◽  
pp. 5553
Author(s):  
Kinley Wangdi ◽  
Kinley Penjor ◽  
Tobgyal ◽  
Saranath Lawpoolsri ◽  
Ric N. Price ◽  
...  
Keyword(s):  
Control Program ◽  
Space Time ◽  
Data Repository ◽  
Spatial Clusters ◽  
Scan Statistic ◽  
Disease Control Program ◽  
Risk Areas ◽  
Vector Borne ◽  
Program Data ◽  
Time Scan

Malaria in Bhutan has fallen significantly over the last decade. As Bhutan attempts to eliminate malaria in 2022, this study aimed to characterize the space–time clustering of malaria from 2010 to 2019. Malaria data were obtained from the Bhutan Vector-Borne Disease Control Program data repository. Spatial and space–time cluster analyses of Plasmodium falciparum and Plasmodium vivax cases were conducted at the sub-district level from 2010 to 2019 using Kulldorff’s space–time scan statistic. A total of 768 confirmed malaria cases, including 454 (59%) P. vivax cases, were reported in Bhutan during the study period. Significant temporal clusters of cases caused by both species were identified between April and September. The most likely spatial clusters were detected in the central part of Bhutan throughout the study period. The most likely space–time cluster was in Sarpang District and neighboring districts between January 2010 to June 2012 for cases of infection with both species. The most likely cluster for P. falciparum infection had a radius of 50.4 km and included 26 sub-districts with a relative risk (RR) of 32.7. The most likely cluster for P. vivax infection had a radius of 33.6 km with 11 sub-districts and RR of 27.7. Three secondary space–time clusters were detected in other parts of Bhutan. Spatial and space–time cluster analysis identified high-risk areas and periods for both P. vivax and P. falciparum malaria. Both malaria types showed significant spatial and spatiotemporal variations. Operational research to understand the drivers of residual transmission in hotspot sub-districts will help to overcome the final challenges of malaria elimination in Bhutan.

scholarly journals An unconditional space–time scan statistic for ZIP‐distributed data

2018 ◽  
Vol 46 (1) ◽  
pp. 142-159 ◽  
Author(s):  
Benjamin Allévius ◽  
Michael Höhle
Keyword(s):  
Space Time ◽  
Distributed Data ◽  
Scan Statistic ◽  
Time Scan

Rapid detection of COVID-19 clusters in the United States using a prospective space-time scan statistic

2020 ◽  
Vol 12 (1) ◽  
pp. 27-33
Author(s):  
Alexander Hohl ◽  
Eric Delmelle ◽  
Michael Desjardins
Keyword(s):  
United States ◽  
Rapid Detection ◽  
The United States ◽  
Space Time ◽  
Scan Statistic ◽  
Time Scan

scholarly journals Impacts COVID-19 pandemic Diseases on Ethiopian Agriculture, Food Systems, Industries, and Mitigation and Adaptation Strategy

2020 ◽  
Vol 1 (1) ◽  
pp. 18-33
Author(s):  
Suleyman Abdureman Omer ◽  
Nuradin Abdi Hassen
Keyword(s):  
Food Security ◽  
Food Systems ◽  
Developed Countries ◽  
Adaptation Strategy ◽  
Data Generation ◽  
Least Developed Countries ◽  
Movement Restriction ◽  
Mitigation And Adaptation ◽  
Agriculture And Food ◽  
Desk Review

The COVID-19 pandemic is a recent outbreak in almost all parts of the world including Ethiopia influencing the socio-economy of people and mainly threatening the agriculture and food security of the least developed countries. The current desk review and opinion synthesis by a multi-disciplinary team of experts from Haramaya University aimed at assessing the probable impact of the virus on the Ethiopian agriculture and food security and suggesting the possible mitigation and adaptation strategies to all responsible. Experts’ opinion and desk review of existing information were employed for the analysis and conclusions drawn, due to the difficulty of data generation at this time of movement restriction and poor database availability on websites of relevant institutions. Accordingly, the information gathered were synthesised and described following the major stages of food supply chains as production, handling and storage, processing and packaging, distribution and marketing, and consumption are key messages drawn from the overall assessment.

scholarly journals Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters

2020 ◽  
Vol 118 ◽  
pp. 102202 ◽  
Author(s):  
M.R. Desjardins ◽  
A. Hohl ◽  
E.M. Delmelle
Keyword(s):  
United States ◽  
The United States ◽  
Space Time ◽  
Scan Statistic ◽  
Time Scan

A Space-Time Scan Statistic for Detecting Emerging Outbreaks

Biometrics ◽  
2010 ◽  
Vol 67 (1) ◽  
pp. 106-115 ◽  
Author(s):  
Toshiro Tango ◽  
Kunihiko Takahashi ◽  
Kazuaki Kohriyama
Keyword(s):  
Space Time ◽  
Scan Statistic ◽  
Time Scan

scholarly journals Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States

2020 ◽  
Vol 34 ◽  
pp. 100354 ◽  
Author(s):  
Alexander Hohl ◽  
Eric M. Delmelle ◽  
Michael R. Desjardins ◽  
Yu Lan
Keyword(s):  
United States ◽  
The United States ◽  
Space Time ◽  
Scan Statistic ◽  
Time Scan

scholarly journals Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico.

1998 ◽  
Vol 88 (9) ◽  
pp. 1377-1380 ◽  
Author(s):  
M Kulldorff ◽  
W F Athas ◽  
E J Feurer ◽  
B A Miller ◽  
C R Key
Keyword(s):  
New Mexico ◽  
Brain Cancer ◽  
Space Time ◽  
Scan Statistic ◽  
Los Alamos ◽  
Time Scan

scholarly journals Applying a Prospective Space-Time Scan Statistic to Examine the Evolution of COVID-19 Clusters in the State of São Paulo, Brazil

2020 ◽  
Author(s):  
R.V. Ferreira ◽  
M.R. Martines ◽  
R.H. Toppa ◽  
L.M. Assunção ◽  
M.R. Desjardins ◽  
...  
Keyword(s):  
Public Management ◽  
Sao Paulo ◽  
Space Time ◽  
The State ◽  
List Type ◽  
São Paulo ◽  
Significant Cluster ◽  
Scan Statistic ◽  
First Case ◽  
Time Scan

AbstractWe present the first geographic study that uses space-time statistics to monitor COVID-19 in Brazil. The first cases of COVID-19 were confirmed in December 2019 in Wuhan, China, caused by the contamination of the SARS-CoV-2 virus, and quickly turned into a pandemic. In Brazil, the first case occurred on January 23rd, 2020 but was officially reported by the Brazilian Ministry of Health on February 25th. Since then, the number of deaths and people infected by COVID-19 in Brazil have been steadily increasing. Despite the underreporting of coronavirus cases by government agencies across the country, the State of São Paulo has the highest rate among all Brazilian States. Thus, it is essential to detect which areas contain the highest concentration of COVID-19 to implement public policies, to mitigate the spread of the epidemic. To identify these critical areas, we utilized daily confirmed case data from the Brasil.IO website between February 25th, 2020 to May 5th, 2020; which were aggregated to the municipality level. A prospective space-time scan statistic was applied to evaluate possible active clusters in three different time periods. The results visualize the space-time evolution and dynamics of COVID-19 clusters in the State of São Paulo. Since the first study period, the results highlight approximately 4.6 times the number of municipalities belonging to a significant cluster with a RR>1 on May 5th. These results can inform health authorities and public management to take the necessary measures to minimize the transmission of COVID-19 and track the evolution of significant space-time clusters.HIGHLIGHTSProspective space-time statistics can improve COVID-19 surveillance in BrazilAll statistically significant clusters are located near São Paulo MunicipalityThere are municipalities with relative risk highest than one in the countryside4.6 times the number of municipalities belong to a significant cluster on May 5th

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