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Background. Malaria is known to cause severe health consequences due to its marked effects and alteration on the haematological parameters of infected individuals. This study evaluated the haematological profile of adult individuals infected with the malaria parasite. Methods. A retrospective study was conducted using archived data of malaria positive cases from January 2017 to March 15, 2019. Data retrieved included subjects’ demographics, malaria parasite count, malaria parasite species, and full blood count parameters. A total of 236 malaria positive subjects were included in the study. Results. The study showed that more females were infected with the malaria parasite than males (69.07% and 30.93%, respectively). A total of 87.3% of the study population were infected with Plasmodium falciparum as compared to 12.7% infected with Plasmodium malariae. The commonest haematological abnormalities that were seen in this study were lymphopenia (56.78%), anaemia (55.51%), thrombocytopenia (47.46%), eosinopenia (45.76%), neutropenia (29.24%), monocytosis (21.19%), and leucocytosis (17.37%) in the infected subjects. The mean platelet count of P. falciparum-infected subjects was decreased as compared to the mean platelet count of P. malariae-infected subjects. There was a significant (P value <0.05) decrease in the number of platelet count with every unit increase in parasite density. Conclusion. Study participants infected with malaria demonstrated vital changes in haematological parameters with anaemia, thrombocytopenia, lymphopenia, monocytosis, and eosinopenia being the most important predictors of malaria infection especially with P. falciparum species.
Background. Malaria is known to cause severe health consequences due to its marked effects and alteration on the haematological parameters of infected individuals. This study evaluated the haematological profile of adult individuals infected with the malaria parasite. Methods. A retrospective study was conducted using archived data of malaria positive cases from January 2017 to March 15, 2019. Data retrieved included subjects’ demographics, malaria parasite count, malaria parasite species, and full blood count parameters. A total of 236 malaria positive subjects were included in the study. Results. The study showed that more females were infected with the malaria parasite than males (69.07% and 30.93%, respectively). A total of 87.3% of the study population were infected with Plasmodium falciparum as compared to 12.7% infected with Plasmodium malariae. The commonest haematological abnormalities that were seen in this study were lymphopenia (56.78%), anaemia (55.51%), thrombocytopenia (47.46%), eosinopenia (45.76%), neutropenia (29.24%), monocytosis (21.19%), and leucocytosis (17.37%) in the infected subjects. The mean platelet count of P. falciparum-infected subjects was decreased as compared to the mean platelet count of P. malariae-infected subjects. There was a significant (P value <0.05) decrease in the number of platelet count with every unit increase in parasite density. Conclusion. Study participants infected with malaria demonstrated vital changes in haematological parameters with anaemia, thrombocytopenia, lymphopenia, monocytosis, and eosinopenia being the most important predictors of malaria infection especially with P. falciparum species.
Background: Malaria continues to be a major public health problem in Malawi and the greatest load of mortality and morbidity occurs in children five years and under. However, there is no information yet regarding trends and predictions of malaria incidence in children five years and under at district hospital level, particularly at Nsanje district hospital. Aim: Therefore, this study aimed at investigating the trends of malaria morbidity and mortality in order to design appropriate interventions on the best approach to contain the disease in the near future. Methodology: Trend analysis of malaria morbidity and mortality together with time series analysis using the SARIMA (Seasonal Autoregressive Integrated Moving Average) model was used to predict malaria incidence in Nsanje district. Results: The SARIMA model used malaria cases from 2015 to 2019 and created the best model to forecast the malaria cases in Nsanje from 2020 to 2022. An SARIMA (0, 1, 2) (0,1,1)12 was suitable for forecasting the incidence of malaria for Nsanje. Conclusion: The mortality and morbidity trend showed that malaria cases were growing at a fluctuating rate at Nsanje district hospital. The relative errors between the actual values and predicted values indicated that the predicted values matched the actual values well. Therefore, the model proved that it was adequate to forecast monthly malaria cases and it had a good fit, hence, was appropriate for this study
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