Assessing measles risk transmission in Iran: a utilization of the World Health Organization's programmatic risk assessment tool,2022

被引:0
|
作者
Dashti, Elham [1 ]
Karami, Manoochehr [1 ,2 ]
Zahraei, Seyed Mohsen [3 ]
Gharibnavaz, Hassan [1 ]
Sabouri, Azam [3 ]
Zavareh, Fatemeh Azimian [3 ]
Delpisheh, Ali [1 ,4 ]
机构
[1] Shahid Beheshti Univ Med Sci, Sch Publ Hlth & Safety, Dept Epidemiol, Tehran, Iran
[2] Shahid Beheshti Univ Med Sci, Environm & Occupat Hazards Control Res Ctr, Tehran, Iran
[3] Minist Hlth & Med Educ, Ctr Communicable Dis Control, Tehran, Iran
[4] Shahid Beheshti Univ Med Sci, Safety Promot & Injury Prevent Res Ctr, Tehran, Iran
关键词
Risk assessment tool; Measles transmission; Iran; Risk assessment; ASSESSMENT TOOL; IMMUNIZATION; EXPERIENCE;
D O I
10.1186/s12879-024-09834-8
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
BackgroundDespite successful efforts to eliminate measles in Iran, imported measles cases continue to be reported. Because measles is endemic in neighboring countries. This research aims to evaluate the risk of measles transmission in different regions of Iran.MethodsMeasles case-based surveillance data of the Expanded Program of Immunization containing 31 provinces and 463 districts from 2019 to 2021 were assessed. The WHO Measles Programmatic Risk Assessment tool was used to evaluate the risk of disease transmission in four domains: population immunity, surveillance quality, program delivery performance, and threat assessment. scores were categorized as low, medium, high, or very high risk.ResultsDuring 2019-2021, the average incidence of measles was 1.9 per 1 million. Chabahar and Mashhad with 76 and ./6per million reported the highest and lowest incidence respectively. All 463 districts were categorized as low risk in risk assessment. Andimeshk, Chabahar, and Bojnurd obtained the highest risk scores with 27, 24, and 25 respectively. All districts were classified as low risk for population immunity. The average coverage of (MMR1) and (MMR2) was 95% or higher. All districts received the minimum points for surveillance quality.ConclusionAll regions are placed at a low level of disease transmission risk. However, the tool is not able to assess the risk at the rural or peripheral sectors level. The indicators used in this tool are the same for all countries with different epidemiological features (elimination, endemic). Sensitivity analysis can optimize the use of this tool for countries with different disease conditions.
引用
收藏
页数:27
相关论文
共 50 条
  • [1] Estimation of measles risk using the World Health Organization Measles Programmatic Risk Assessment Tool, Iran
    Mohammadbeigi, Abolfazl
    Zahraei, Seyed Mohsen
    Asgarian, Azadeh
    Afrashteh, Sima
    Mohammadsalehi, Narges
    Khazaei, Salman
    Ansari, Hossein
    HELIYON, 2018, 4 (11):
  • [2] The World Health Organization Measles Programmatic Risk Assessment ToolRomania, 2015
    Kriss, Jennifer L.
    Stanescu, Aurora
    Pistol, Adriana
    Butu, Cassandra
    Goodson, James L.
    RISK ANALYSIS, 2017, 37 (06) : 1096 - 1107
  • [3] Application of the World Health Organization Programmatic Assessment Tool for Risk of Measles Virus Transmission-Lessons Learned from a Measles Outbreak in Senegal
    Harris, Jennifer B.
    Badiane, Ousseynou
    Lam, Eugene
    Nicholson, Jennifer
    Ba, Ibrahim Oumar
    Diallo, Aliou
    Fall, Amadou
    Masresha, Balcha G.
    Goodson, James L.
    RISK ANALYSIS, 2016, 36 (09) : 1708 - 1717
  • [4] Development of the World Health Organization Measles Programmatic Risk Assessment Tool Using Experience from the 2009 Measles Outbreak in Namibia
    Kriss, Jennifer L.
    De Wee, Roselina J.
    Lam, Eugene
    Kaiser, Reinhard
    Shibeshi, Messeret E.
    Ndevaetela, Emmy-Else
    Muroua, Clementine
    Shapumba, Nicholaus
    Masresha, Balcha G.
    Goodson, James L.
    RISK ANALYSIS, 2017, 37 (06) : 1072 - 1081
  • [5] Using the World Health Organization Measles Programmatic Risk Assessment Tool for Monitoring of Supplemental Immunization Activities in the Philippines
    Ducusin, Maria Joyce U.
    de Quiroz-Castro, Maricel
    Roesel, Sigrun
    Garcia, Luzviminda C.
    Cecilio-Elfa, Dulce
    Schluter, W. William
    Goodson, James L.
    Lam, Eugene
    RISK ANALYSIS, 2017, 37 (06) : 1082 - 1095
  • [6] The World Health Organization Measles Programmatic Risk Assessment ToolPilot Testing in India, 2014
    Goel, Kapil
    Naithani, Saroj
    Bhatt, Dheeraj
    Khera, Ajay
    Sharapov, Umid M.
    Kriss, Jennifer L.
    Goodson, James L.
    Laserson, Kayla F.
    Goel, Parul
    Kumar, R. Mohan
    Chauhan, L. S.
    RISK ANALYSIS, 2017, 37 (06) : 1063 - 1071
  • [7] Development of a District-Level Programmatic Assessment Tool for Risk of Measles Virus Transmission
    Lam, Eugene
    Schluter, W. William
    Masresha, Balcha G.
    Teleb, Nadia
    Bravo-Alcantara, Pamela
    Shefer, Abigail
    Jankovic, Dragan
    McFarland, Jeffrey
    Elfakki, Eltayeb
    Takashima, Yoshihiro
    Perry, Robert T.
    Dabbagh, Alya J.
    Banerjee, Kaushik
    Strebel, Peter M.
    Goodson, James L.
    RISK ANALYSIS, 2017, 37 (06) : 1052 - 1062
  • [8] USE OF THE WORLD HEALTH ORGANIZATION FRACTURE RISK ASSESSMENT TOOL IN ANKYLOSING SPONDYLITIS
    Wallis, Dinny
    Thomas, Amanda
    Hill, Ingrid
    France, Brisa
    Sengupta, Raj
    RHEUMATOLOGY, 2012, 51 : 87 - 87
  • [9] World Health Organization fracture risk assessment tool in the assessment of fractures after falls in hospital
    Shin-ichi Toyabe
    BMC Health Services Research, 10
  • [10] World Health Organization fracture risk assessment tool in the assessment of fractures after falls in hospital
    Toyabe, Shin-ichi
    BMC HEALTH SERVICES RESEARCH, 2010, 10