Showing posts with label malaria transmission. Show all posts
Showing posts with label malaria transmission. Show all posts

Friday, 24 October 2025

Mathematical Modelling and Analysis of Malaria Transmission Dynamics among Children under Five with Early and Late Treatment Interventions | Chapter 2 | Mathematics and Computer Science: Research Updates Vol. 7

 

Malaria, a life-threatening disease caused by Plasmodium parasites transmitted through the bites of infected Anopheles mosquitoes, poses a persistent public health challenge in Nigeria due to its complex transmission dynamics. Mathematical modeling provides a robust framework to unravel the complexities of malaria transmission, enabling predictions of disease dynamics and evaluation of control measures. This study develops a compartmental SEIIR-SEI model to evaluate the impact of early (λ1) and late (λ2) treatment interventions on malaria transmission among children under 5, aiming to guide effective control strategies. Parameterized with Nigerian malaria case data (2007–2021), the model integrates human and mosquito populations to examine how treatment timing affects the basic reproduction number (R0) and disease prevalence. The methodology encompasses model formulation, assumptions, parameter estimation, analytical methods, and numerical simulations. Using stability analysis, sensitivity analysis, and numerical simulations, we find a baseline R0 = 2.24, indicating endemicity. Early treatment reduces this to R0,λ1 = 1.46, outperforming late treatment (R0,2 = 1.65). Sensitivity analysis highlights mosquito biting rates ((b) and λ1 as key drivers of R0. Simulations show that 60–80% early treatment coverage (λ1 ≥ 0.6) within 24 hours significantly lowers prevalence within 120 days, unlike 100% late treatment (λ2 = 1.0). The disease-free equilibrium is stable when R0 < 1, achievable with high λ1. Rapid diagnosis, Artemisininbased Combination Therapies, and vector control are critical for eradication. Policymakers should enhance healthcare access and surveillance to reduce Nigeria’s malaria burden. These findings provide a rigorous, data-driven foundation for policymakers to optimize malaria control programs, reducing morbidity, mortality, and economic burdens in endemic regions. Future studies should explore fractionalorder models or spatial dynamics to further refine intervention strategies.

 

Author(s) Details

 

D.B. Opaginni
Department of Mathematical Sciences, University of Abuja, FCT, Nigeria.

 

M.O. Durojaye
Department of Mathematical Sciences, University of Abuja, FCT, Nigeria.

 

Please see the book here :- https://doi.org/10.9734/bpi/mcsru/v7/6198

Saturday, 13 August 2022

Population Dynamics, Infectivity and Longevity of Anopheles Mosquitoes in Relation to Malaria Transmission in Bali District, Taraba State | Book Publisher International

We contacted and notified the local leaders of the research locations, Daniya Bali, Fundalara, and Gazabubarkeji in the Bali district of the Bali Local Government in Taraba state. Before the start of the mosquito sampling in the final week of June 2018, a preliminary survey of the three villages was done and the verbal consent of the heads of households was requested.

In the three riverine communities of Daniya Bali, Fundalara, and Gazabubarkeji between June and December 2018, mosquitoes were collected using non-residual insecticide-pyrethrum (Spread Sheet Collection). It was noticed how many persons spent the night in the room. Mosquitoes that were collected and recently preserved were sorted and morphologically recognised down to the species level. Extracted from fed and unfed Anopheles gambiae, the ovaries were swiftly moved to a drop of distilled water on a slide, where they were quickly checked for tracheal skein and categorised as parous or nulliparous under high magnification. A biochemical approach was used to determine the Human Blood Index (HBI) and Plasmodium sporozoite infection of the fed Anopheles gambiae (ELISA).

Four mosquito species, totaling 614, including Anopheles gambiae complex 589 (96.0%), Mansonia uniformis 11 (1.8%), Culex quinquefasciatus 12 (1.9%), and Aedes aegypti 2 (0.3%), were identified morphologically. With 325 (52.9%) mosquitoes, Fundalara village has the greatest mosquito population, followed by Gazabubarkeji with 194 (31.6%). Daniya Bali 95 had the lowest percentage (15.5%). ANOVA revealed a significant difference (P 0.05) between mosquito abundance and the research locations. The seasons' prevalence of mosquito catch revealed that there were 509 (82.9%) more than 105 (17.1%) during the dry season. Female mosquitoes were more prevalent 510 than male mosquitoes 104 collected indoors, according to sex. 191 of the 485 Anopheles gambiae were blood fed, and their HBI was 1, their MBR was 1.93 bites per man per night, their sporozoite rate (SR) was 0.005, and their infectious biting rate was 0.01. Only during the wet season were the SR and IBR measured. Additionally, the MBR during the wet season was higher than it was during the dry season (0.07 bites per man each night). The T-test revealed a statistically significant variation in mosquito abundance between seasons (P0.05), but not between MBR, SR, or IBR (P>0.05). 485 mature female Anopheles gambiae mosquitoes in total were counted. Wet season 413 (85.2%) had more mosquitoes than dry season 72 (14.8%). During the wet and dry seasons, respectively, there were 4.13 and 0.81 mosquito densities per human. The mosquitoes' seasonal numbers varied significantly (P 0.05). Wet season parous was 0.57, and dry season parous was 0.47. During the rainy and dry seasons, respectively, the probability of daily survival of mosquito individuals were 0.75 and 0.688, although there was no discernible difference (P > 0.05). In the rainy and dry seasons, adult mosquitoes had a life expectancy of 8.0 days and 5.9 days, respectively. This difference was statistically significant (P 0.05). There was no discernible difference between the extrinsic incubation periods for Plasmodium falciparum throughout the wet and dry seasons (P>0.05). The likelihood of mosquitoes surviving long enough to transmit disease increased from 0.02 in the dry season to 0.06 in the wet season. Thus, despite being small, mosquito vectorial capabilities were significantly larger during the wet season (1.98 vs. 0.09; P 0.05) than during the dry season (0.09). Under comparable ecological conditions, it was projected that Anopheles gambiae could transmit Plasmodium vivax twice as well as it could Plasmodium falciparum.

These results suggest that the research area is vulnerable to malaria and other mosquito-borne diseases, with the possibility of greater transmission during the rainy season.

Due to high rates of everyday survival, the Anopheles gambiae population in the Bali district was also dominated by old mosquitoes. This mosquito has a long lifespan in this region, and the favourable climate for Plasmodium growth results in a high vectorial potential for malaria transmission.

Author (s) Details

Lamidi, Babatunde Tajudeen

Department of Science Laboratory Technology, Federal Polytechnic, Bali, Taraba state, Nigeria.

Elijah, M. Iganga

Department of Science Laboratory Technology, Federal Polytechnic, Bali, Taraba state, Nigeria.

Irebanije, J. Francis

Department of Science Laboratory Technology, Federal Polytechnic, Bali, Taraba state, Nigeria.

Damburam, J. Hussaina

Department of Science Laboratory Technology, Federal Polytechnic, Bali, Taraba state, Nigeria.

Dahiru, Faiza

Department of Science Laboratory Technology, Federal Polytechnic, Bali, Taraba state, Nigeria.

 

Please see the link here:-  https://stm.bookpi.org/PDILAMRMTBDTS/issue/view/737