Influence of seasonal variation on reported filarial attacks among people living with lymphedema in Ghana.

BACKGROUND: Lymphatic Filariasis (LF) is a vector-borne neglected tropical disease caused by the filarial nematode parasites that can lead to the disfiguring swelling of the limbs (lymphedema or elephantiasis for late stage) and/or genitalia (hydrocele) in men. Growing evidence suggests that not only are filarial lymphedema patients confronted with huge societal stigma and discrimination, but also experience acute filarial attacks accompanied by swelling of the affected part(s), fever, wounds and peeling of the skin of affected limbs(s). However, the extent to which seasonal variation influence filarial attacks among people with lymphedema was highly speculated without empirical evidence and was thus investigated. METHODS: In light of this, a cross-sectional study where 142 (70.4% females and 29.6% males) lymphedema patients were recruited from 8 established Wuchereria bancrofti endemic communities in the Ahanta West District, Ghana was carried out to investigate the prevalence and seasonal variation (rainy/wet and dry seasons) of acute filarial attacks. Chi-square test was used to test for association between frequency of attacks and seasonality. The STROBE guidelines for reporting cross-sectional studies was adopted. RESULTS: The average lymphedema leg stage was 2.37 and 2.33 for left and right legs, respectively, while mossy lesions, sores and ulcers were observed among 33.1% of patients with late stage disease (elephantiasis). It was found that 97 (68.3%) of the study participants experience filarial attacks during the wet season and 36 (25.4%) reported the incidence of filarial attacks during both seasons (wet and dry) while 9 (6.3%) of the study participants did not experience any attack at all. CONCLUSIONS: Findings from the present study show compelling evidence that the frequency and the prevalence of filarial attacks is significantly increased during wet seasons compared to the dry season.

Fractal-fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics.

This paper proposes a new fractal-fractional age-structure model for the omicron SARS-CoV-2 variant under the Caputo-Fabrizio fractional order derivative. Caputo-Fabrizio fractal-fractional order is particularly successful in modelling real-world phenomena due to its repeated memory effect and ability to capture the exponentially decreasing impact of disease transmission dynamics. We consider two age groups, the first of which has a population under 50 and the second of a population beyond 50. Our results show that at a population dynamics level, there is a high infection and recovery of omicron SARS-CoV-2 variant infection among the population under 50 (Group-1), while a high infection rate and low recovery of omicron SARS-CoV-2 variant infection among the population beyond 50 (Group-2) when the fractal-fractional order is varied.

Fractional-Order Ebola-Malaria Coinfection Model with a Focus on Detection and Treatment Rate.

Coinfection of Ebola virus and malaria is widespread, particularly in impoverished areas where malaria is already ubiquitous. Epidemics of Ebola virus disease arise on a sporadic basis in African nations with a high malaria burden. An observational study discovered that patients in Sierra Leone's Ebola treatment centers were routinely infected with malaria parasites, increasing the risk of death. In this paper, we study Ebola-malaria coinfections under the generalized Mittag-Leffler kernel fractional derivative. The Banach fixed point theorem and the Krasnoselskii type are used to analyse the model's existence and uniqueness. We discuss the model stability using the Hyers-Ulam functional analysis. The numerical scheme for the Ebola-malaria coinfections using Lagrange interpolation is presented. The numerical trajectories show that the prevalence of Ebola-malaria coinfections ranged from low to moderate depending on memory. This means that controlling the disease requires adequate knowledge of the past history of the dynamics of both malaria and Ebola. The graphical dynamics of the detection rate indicate that a variation in the detection rate only affects the following compartments: individuals that are latently infected with the Ebola, Ebola virus afflicted people who went unnoticed, individuals who have been infected with the Ebola virus and have been diagnosed with the disease, and persons undergoing Ebola virus therapy.