Background: Effective case management, identification of resistance, and disease control need continuous monitoring of malaria infection and antimalarial medication effectiveness.
The goal of this study was to analyse malaria infection and antimalarial effectiveness among people who visited drugstores for malaria treatment in Port Harcourt and its surrounds in Rivers State, Nigeria.
Materials and Methods: Whole blood was obtained at random from people visiting 24 pharmacy stores in three distinct locations in Port Harcourt for malaria treatment and analysed using microscopy and quick diagnostic procedures.
The total prevalence of (P. falciparum) malaria was observed at 22.8 percent among 633 subjects. Mile IV (Rumueme) had the highest infection rate (30.8%), followed by Rumuosi (23.1%), and D/Line area (14.5%), out of a total of 221 individuals per site. Malaria incidence was considerably different in the study area (X2 = 16.69; p = 0.001). In the study locations, there was no significant variation in the degree of malaria parasite infection. To treat suspected malaria, seven different medicines were purchased. Coatem was purchased by 177 (26.7%) participants, whereas Lonart was purchased by 187 (28.3%). Lumartem was second with 133 (20.1%), followed by P.alaxin with 83 (12.5%), Amarla with 19 (2.9%), and artesunate with 57. (8.6 percent ). Those that tested positive bought all of the antimalarials. Lonart 11 (34.37 percent), Lumartem 25 (36.8%), and Malareich 19 (31.3 percent) were the most popular drugs in the D/Line, Mile IV, and Rumuosi cluster regions, respectively. The antimalarials purchased had a substantial difference. Only 59.6% of those who were examined returned for a follow-up test, and they all came back negative.
Conclusion: Malaria was prevalent among the study participants, and ACT was the most often purchased antimalarial drug. The level of compliance with the usage of ACT is outstanding, albeit not yet 100 percent. Malaria patients should be encouraged to take a test following treatment to ensure optimal case management and resistance identification.
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