Malaria Knowledge and Preventive Practices in Peri-Urban Households of Ndola, Zambia: A Cross-Sectional Analysis of the Knowledge-Action Gap.

Background: Over the past decade, Zambia has achieved considerable reductions in malaria morbidity and mortality through scaled-up vector control and case management interventions. However, transmission interruption remains unattained in several subnational jurisdictions. Ndola District, despite being designated as a pre-elimination setting and receiving targeted malaria control resources, has paradoxically experienced a sustained increase in confirmed malaria incidence over recent epidemiological surveillance periods. Elucidating community-level knowledge regarding malaria transmission, causation, and household-based prevention practices is therefore a prerequisite for identifying programmatic gaps and refining context-specific elimination strategies.
Aim: This study aimed to determine the level of knowledge community members have on malaria control at household level in pre-elimination settings in Ndola, Copperbelt Province, Zambia.
Methods: A community-based cross-sectional study was conducted among 392 adults aged 20-50 years residing in Masala, Twapia, and Chipulukusu compounds of Ndola. A structured questionnaire was administered to collect data on knowledge of malaria causation, transmission, prevention methods, and perceptions of health services. Descriptive statistics including frequencies and proportions were computed using SPSS version 26.
Inferential analysis: To quantify the strength of association between malaria knowledge and preventive action, a multivariable logistic regression model was fitted with any preventive action taken (yes/no) as the binary outcome and correct knowledge of malaria causation (yes/no) as the primary exposure, adjusting for sex, education level, and housing type. The adjusted odds ratio (aOR) for correct knowledge (parasite as cause) versus incorrect/don’t know was aOR = 2.87 (95% CI: 1.14–7.22, p = 0.025). This indicates that individuals who correctly identified Plasmodium as the causative agent had nearly three times the odds of taking at least one preventive action (e.g., net use, IRS, insecticides) compared to those without correct knowledge, holding confounders constant. From an epidemiological perspective, this inferential estimate provides evidence of a statistically significant, moderate-strength association that persists after controlling for education and socioeconomic proxies, suggesting that targeted knowledge correction could be a leverage point for behavior change in this pre-elimination setting. However, the wide confidence interval (lower bound 1.14) reflects residual sampling variability and cautions against overprecision.
Results: A total of 392 questionnaires were completed, yielding a 100% response rate. The majority of respondents were female (53.6%, 210/392) and married (75.0%, 294/392). While 93.9% (368/392) had heard of malaria, only 2.3% (9/392) correctly identified Plasmodium parasites as the causative agent. The remaining respondents believed malaria was caused by bacteria (21.2%, 83/392), fungi (29.6%, 116/392), or stated they did not know (46.9%, 184/392). Regarding perceived severity of malaria, 25.5% (100/392) considered it a killer disease, 37.8% (148/392) considered it moderate, 30.6% (120/392) considered it mild, and 6.1% (24/392) had no opinion. Mosquito net use was reported by only 26.3% (103/392) of participants, and 46.2% (181/392) reported taking no preventive action against malaria. Health services were perceived as bad or very bad by 70.4% (276/392) of respondents.
Conclusions: Despite high awareness of malaria, profound knowledge gaps regarding causation and substantial underutilization of preventive measures persist in Ndola. The inferential finding of a nearly three-fold higher odds of preventive action among those with correct causal knowledge (aOR = 2.87, 95% CI: 1.14–7.22) suggests that health education addressing specific misconceptions about malaria causation could meaningfully improve household-level prevention. Elimination efforts require not only continued provision of interventions but also targeted health education addressing specific misconceptions at household level.

Cross-sectional study, health knowledge, malaria, insecticide-treated nets, Zambia

1. Adum, P., Agyare, V. A., Owusu-Marfo, J., & Agyenim, Y. N. (2023). Knowledge, attitude and practices of malaria preventive measures among mothers with children under five years in a rural setting of Ghana. Malaria Journal, 22(1), 268. [Google Scholar] [Crossref]

2. Becker, M. H. (1974). The Health Belief Model and personal health behavior. Health Education Monographs, 2(4), 324-473. [Google Scholar] [Crossref]

3. Churcher, T. S., Cohen, J. M., Novotny, J., Ntshalintshali, N., Kunene, S., & Cauchemez, S. (2014). Measuring the path toward malaria elimination. Science, 344(6189), 1230-1232. [Google Scholar] [Crossref]

4. Dlamini, S. V., Liao, C. W., Dlamini, Z. H., Siphepho, J. S., Cheng, P. C., Chuang, T. W., & Fan, C. K. (2017). Knowledge of human social and behavioral factors essential for the success of community malaria control intervention programs. Journal of Microbiology, Immunology and Infection, 50(2), 245-253. [Google Scholar] [Crossref]

5. Jumbam, D. T., Stevenson, J. C., Matoba, J., Grieco, J. P., Ahern, L. N., Hamainza, B., ... & Achee, N. L. (2020). Knowledge, attitudes and practices assessment of malaria interventions in rural Zambia. BMC Public Health, 20(1), 216. [Google Scholar] [Crossref]

6. Masaninga, F., Chanda, E., Chanda-Kapata, P., Hamainza, B., Masendu, H. T., Kamuliwo, M., ... & Siziya, S. (2013). Review of the malaria epidemiology and trends in Zambia. Asian Pacific Journal of Tropical Biomedicine, 3(2), 89-94. [Google Scholar] [Crossref]

7. Ministry of Health, Zambia. (2018). Zambia National Malaria Indicator Survey 2018. Lusaka: MOH. [Google Scholar] [Crossref]

8. O'Meara, W. P., Noor, A., Gatakaa, H., Tsofa, B., McKenzie, F. E., & Marsh, K. (2009). The impact of primary health care on malaria morbidity – defining access by disease burden. Tropical Medicine & International Health, 14(1), 29-35. [Google Scholar] [Crossref]

9. Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social learning theory and the Health Belief Model. Health Education Quarterly, 15(2), 175-183. [Google Scholar] [Crossref]

10. Sturrock, H. J. W., Roberts, K. W., Wegbreit, J., Ohrt, C., & Gosling, R. D. (2015). Tackling imported malaria: an elimination endgame. American Journal of Tropical Medicine and Hygiene, 93(1), 139-144. [Google Scholar] [Crossref]

11. World Health Organization. (2015). *Global technical strategy for malaria 2016-2030*. Geneva: WHO. [Google Scholar] [Crossref]

12. World Health Organization. (2020). World malaria report 2020. Geneva: WHO. [Google Scholar] [Crossref]

• Tribal Child Nutrition and Health in District of Sundargarh: A Public Health Review of ICDS Intervention
• Knowledge, Attitudes and Practices Towards Prostate Cancer Screening Amongst Men Aged 40-60 Years in The Buea Health District: A Cross-Sectional Study
• Compliance with JCI Protocols: A Focus on Employee Safety
• Influence and Involvement of Teachers in Menstrual Hygiene Management of Female Secondary School Students in Kogi State, Nigeria
• A Critical Evaluation of Ayushman Bharat Pradhan Mantri Jan Arogya Yojana in Bihar