Recently, meningitis outbreaks have posed substantial public health issues across the world, prompting effective preventative and control measures. Therefore, this work proposes a unique method for estimating meningitis incidence by incorporating atmospheric data into a predictive model, christened as climate-based predictive meningitis model (CBPMM). The CBPMM is created using machine learning formalities, with meteorological data serving as key component of the predictor. The model incorporates powerful prediction techniques that analyze historical data and environmental patterns comprehensively and thus, provide useful insights for early identification and proactive intervention strategies. With infection transmission rate at 0.88, carrier natural recovery rate 0.06, and the efficacy of treatment is 0.001, ; it implies that the infectious disease persists in the community. However, when ; that is, the disease is controllable. The CBPMM marks a huge step forward in meningitis surveillance, providing healthcare authorities with information to promptly limit the effect of outbreaks. Keywords: Forecasting, Meningitis outbreaks, Environmental factors, and Machine learning technique Read more

Communities are concerned about controlling, preventing and handling infectious diseases due to recent epidemic outbreaks . Meningitis, an inflammation of the membranes surrounding the brain and spinal cord, is a significant risk in Nigeria. It can cause death within hours of infection with average case fatality rate of 10 percent. To prevent meningitis outbreaks, this paper focuses on using an Artificial Neural network (ANN) to predict outbreak of meningitis based on climatological factors. Previous research has shown that climate plays a major role in these outbreaks. The study found that Levenberg-Marquarait ANN algorithm was the best with the lowest prediction error and fewer iterations . High temperature and low humidity were identified as major triggers for meningitis outbreaks. It is crucial to address these factors to prevent future outbreaks and protect the community. Read more

Meningitis continues to be a significant public health challenge in Nigeria, leading to substantial morbidity and mortality rates. Effective control and prevention strategies are crucial in mitigating the impact of this infectious disease. It is in the light of this that this study therefore, from an analytical audience perspective, examines health communication as a viable tool in the control and prevention of meningitis in Nigeria. The objective of this study is basically to examine the impact of health communication interventions on the knowledge and preventive behavior related to meningitis among the target audience in Nigeria. This study is anchored on the attitude change theory; and data were collected through the use of questionnaires. Findings from this study show that health communication interventions have been impactful because it has influenced the knowledge and preventive behavior of the respondents as regards to the control and prevention of meningitis. The study also revealed that health communication strategies have been highly effective in the control and prevention of meningitis in Nigeria. This study recommends that in order to enhance the effectiveness of health communication as a viable tool in the control and prevention of meningitis in Nigeria, the multi-channel communication approaches should be strengthened. Read more