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RISS 인기검색어
- 검색키워드
- 저자 : Abraham Priya (검색결과 3 건)
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Kunasagran Priya Dharishini,Mokti Khalid,Ibrahim Mohd Yusof,Rahim Syed Sharizman Syed Abdul,Robinson Freddie,Muyou Adora J,Mujin Sheila Miriam,Ali Nabihah,Chao Gary Goh Chun,Nasib Rudi,Loong Abraham C 대한가정의학회 2024 Korean Journal of Family Medicine Vol.45 No.1
The coronavirus disease (COVID-19) pandemic has led to an alarming increase in domestic violence against wom-en owing to lockdown measures and limited access to support services. This article provides insights into the global prevalence of domestic violence, barriers to seeking help, its impact on women and children, and the best practices implemented worldwide. Domestic violence encompasses various forms of abuse; many young women experi-ence partner violence. Barriers to seeking help include fear, financial constraints, lack of awareness of available ser-vices, and distrust among stakeholders. The consequences of domestic violence affect the mental health of both mothers and children. Countries have increased shelter funding and developed innovative protocols to reach sur-vivors and address this issue. However, the healthcare sector’s involvement in addressing domestic violence has been limited. This review advocates collaboration among healthcare institutions and government bodies. Key rec-ommendations include utilizing telehealth services, implementing comprehensive training programs, establishing effective referral systems, enhancing health education, developing a domestic violence registry, improving the re-sponses of law enforcement and justice systems through healthcare integration, promoting data sharing, and con-ducting further research. Healthcare systems should recognize domestic violence as a public health concern and detect, prevent, and intervene in cases to support survivors.
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Shil Pratip,Atre Nitin M.,Patil Avinash A.,Tandale Babasaheb V.,Abraham Priya 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1
SARS-CoV-2 or COVID-19 was introduced into India by multiple sources generating local clusters and leading to the nationwide spread. A retrospective study has been conducted on the epidemiological features and spatial spread of COVID-19 in India during February 2020–March 2021. For each district, the cumulative number of confirmed COVID-19 cases were fitted to exponential growth model for the initial phase of the outbreak (the first 7–15 days). From the estimated growth rate, epidemiological parameters like the Basic reproduction number (R0) and epidemic doubling time (s) were determined. Using Q-GIS software, we have generated the all India distribution maps for R0 and s. COVID-19 spread rapidly covering majority of the districts of India between March and June 2020. As on 1st March 2021, a total of 715 out of 717 districts have been affected. The R0 range is at par with the global average. A few districts, where outbreaks were caused by migrant workers coming home, intense transmission was recorded R0[7. We also found that the spread of COVID-19 was not uniform across the different districts of India. The methodology developed in the study can be used by researchers and public health professionals to analyze and study epidemics in future.
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Shil Pratip,Atre Nitin M.,Patil Avinash A.,Tandale Babasaheb V.,Abraham Priya 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2
SARS-CoV-2 or COVID-19 was introduced into India by multiple sources generating local clusters and leading to the nationwide spread. A retrospective study has been conducted on the epidemiological features and spatial spread of COVID-19 in India during February 2020–March 2021. For each district, the cumulative number of confirmed COVID-19 cases were fitted to exponential growth model for the initial phase of the outbreak (the first 7–15 days). From the estimated growth rate, epidemiological parameters like the Basic reproduction number (R0) and epidemic doubling time (s) were determined. Using Q-GIS software, we have generated the all India distribution maps for R0 and s. COVID-19 spread rapidly covering majority of the districts of India between March and June 2020. As on 1st March 2021, a total of 715 out of 717 districts have been affected. The R0 range is at par with the global average. A few districts, where outbreaks were caused by migrant workers coming home, intense transmission was recorded R0[7. We also found that the spread of COVID-19 was not uniform across the different districts of India. The methodology developed in the study can be used by researchers and public health professionals to analyze and study epidemics in future.
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