Scholarlink

Background <p>Malaria remains a severe, life-threatening disease worldwide, with Sub-Saharan Africa bearing the greatest burden. In Ethiopia, recurrent outbreaks cause substantial morbidity and strain local health systems. During WHO Epidemiologic Week 13 of 2025, Meinit Goldia District experienced a sharp increase in cases with delayed investigation and response. This study aimed to verify the outbreak, identify associated risk factors, and inform targeted control measures.</p> Methods <p>A community-based case–control study was conducted in Meinit Goldia District from 26 March to 30 June 2025. Descriptive analysis used the district linelist of malaria cases and deaths. A multistage cluster sampling technique with proportional allocation was employed. A total of 145 rapid diagnostic test (RDT) confirmed malaria cases and 145 community-based, RDT negative asymptomatic controls were included in the study. Both case and controls were identified through active house-to-house surveillance in malaria-affected kebeles. Data on socio-demographics, ITN utilization, environmental exposures, and malaria knowledge were collected via interviewer-administered questionnaires using Kobo Collect v2025.3.3. Analyses were performed in STATA v17. Variables with <i>P</i> &lt; 0.25 in bivariable analysis entered multivariable logistic regression; significance was set at <i>P</i> &lt; 0.05. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. Firth’s correction was used for exposures with sparse data.</p> Results <p>Review of the line list from the malaria-affected kebeles identified 3,630 laboratory-confirmed malaria cases, yielding an attack rate (AR) of 274.7 cases per 1,000 population in the eight outbreak-affected villages. The highest attack rates were observed among males (288.2 per 1,000 population) and residents of Mehal Dashi village. At the district level, the overall AR was 71.3 cases per 1,000 population. In multivariable analysis, the following variables were independently associated with malaria: Never utilized ITNs (AOR = 4.882; 95% CI: 2.011–11.847), Living near broken glass bottles (AOR = 4.847; 95% CI: 1.692–13.889), Open deep well near household (AOR = 3.735; 95% CI: 1.273–10.956), Poor knowledge of malaria transmission, signs, symptoms, and prevention/control measures (AOR = 2.847; 95% CI: 1.502–5.397), Sometimes utilized ITNs (AOR = 2.617; 95% CI: 1.204–5.692), and Wearing long protective clothing at night (AOR = 0.123; 95% CI: 0.054–0.280).</p> Conclusions <p>The outbreak in Meinit Goldia District was associated with gaps in vector control, local breeding sites, and delayed response. Immediate priorities include targeted ITN distribution and larval source management in high-burden areas, regular IRS, culturally appropriate health education, strengthened early warning and rapid response capacity, and enhanced entomological surveillance.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Malaria Outbreak in Meinit Goldia District, Southwest Ethiopia Peoples Regional State, 2025: Risk factors and epidemiological insights from a case-control study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月26日

查看全文
  • Nigatu Admasu Desta,
  • Simon Fikadu,
  • Gemechu Chemeda,
  • Abraham Lomboro Dimore

摘要

Background

Malaria remains a severe, life-threatening disease worldwide, with Sub-Saharan Africa bearing the greatest burden. In Ethiopia, recurrent outbreaks cause substantial morbidity and strain local health systems. During WHO Epidemiologic Week 13 of 2025, Meinit Goldia District experienced a sharp increase in cases with delayed investigation and response. This study aimed to verify the outbreak, identify associated risk factors, and inform targeted control measures.

Methods

A community-based case–control study was conducted in Meinit Goldia District from 26 March to 30 June 2025. Descriptive analysis used the district linelist of malaria cases and deaths. A multistage cluster sampling technique with proportional allocation was employed. A total of 145 rapid diagnostic test (RDT) confirmed malaria cases and 145 community-based, RDT negative asymptomatic controls were included in the study. Both case and controls were identified through active house-to-house surveillance in malaria-affected kebeles. Data on socio-demographics, ITN utilization, environmental exposures, and malaria knowledge were collected via interviewer-administered questionnaires using Kobo Collect v2025.3.3. Analyses were performed in STATA v17. Variables with P < 0.25 in bivariable analysis entered multivariable logistic regression; significance was set at P < 0.05. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported. Firth’s correction was used for exposures with sparse data.

Results

Review of the line list from the malaria-affected kebeles identified 3,630 laboratory-confirmed malaria cases, yielding an attack rate (AR) of 274.7 cases per 1,000 population in the eight outbreak-affected villages. The highest attack rates were observed among males (288.2 per 1,000 population) and residents of Mehal Dashi village. At the district level, the overall AR was 71.3 cases per 1,000 population. In multivariable analysis, the following variables were independently associated with malaria: Never utilized ITNs (AOR = 4.882; 95% CI: 2.011–11.847), Living near broken glass bottles (AOR = 4.847; 95% CI: 1.692–13.889), Open deep well near household (AOR = 3.735; 95% CI: 1.273–10.956), Poor knowledge of malaria transmission, signs, symptoms, and prevention/control measures (AOR = 2.847; 95% CI: 1.502–5.397), Sometimes utilized ITNs (AOR = 2.617; 95% CI: 1.204–5.692), and Wearing long protective clothing at night (AOR = 0.123; 95% CI: 0.054–0.280).

Conclusions

The outbreak in Meinit Goldia District was associated with gaps in vector control, local breeding sites, and delayed response. Immediate priorities include targeted ITN distribution and larval source management in high-burden areas, regular IRS, culturally appropriate health education, strengthened early warning and rapid response capacity, and enhanced entomological surveillance.