Published May 30, 2020 | Version v1
Journal article Open

Policy Model of Community Adaptation using AHP in the Malaria Endemic Region of Lahat Regency - Indonesia

  • 1. his/her Program of Diploma III Nursing and doctoral program of environmental science, Universitas Negeri Padang, Padang, Indonesia.
  • 2. Department of doctoral program of environmental science, Universitas Negeri Padang, Padang, Indonesia.
  • 3. Department of geography and doctoral program of environmental science, Universitas Negeri Padang, Padang, Indonesia.
  • 1. Publisher

Description

Lahat Regency is a malaria-endemic region, so the research aims to develop a model of policy adaptation of society in the malaria-endemic region to Lahat Regency. This research is a qualitative study by collecting data through interviews and Focus Group Discussion (FGD), which is then processed using Expert Choice that is analyzed by the Analytical Hierarchy Process (AHP) technique. The results showed that there were 3 criteria in determining the priorities of the adaptation policy, i.e the hosts/society, agent/cause of the disease, and vector/environment. The policy Model was compiled using 3 criteria that resulted in successive policy priorities as follows: strengthening of preventive and curative malaria program of local-based (39.8%), strengthening malaria information system through community empowerment (17.4%), strengthening the commitment of central and local governments in sustainability fulfilment of program needs and coordination among related agencies (14.7%), projection of malaria transmission in space and time scale periodically and sustainably based on environmental factors (9%), malaria centre or malaria control centre (6.2%), the program of Chemoppropilaxis as an action against Plasmodium (5.8%), strengthening the capacity of health workers and laboratory personnel (4.2%), and development of the cross-sectoral intervention model (3%). 3 priorities became the main program conducted through a wide range of strategies.

Files

I0855054920.pdf

Files (289.1 kB)

Name Size Download all
md5:1fffa3e20674b01a329e061f467c6567
289.1 kB Preview Download

Additional details

Related works

Is cited by
Journal article: 2394-0913 (ISSN)

Subjects

ISSN
2394-0913
Retrieval Number
I0855054920/2020©BEIESP