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Faecal sludge (FS) management is pertinent to the achievement of sustainable development goal 6.2 around the world; yet it is constrained by urbanisation challenges, waste management complexities, and defective attitudes. These deny communities of the plausible supply of resources from FS. This paper assesses the perception underpinning the occurrence of nonfaecal matter in FS in Ghana. Primary data were obtained from 400 respondents in four communities in Brong Ahafo and Greater Accra Regions of Ghana, using a structured questionnaire. Data were analysed by using STATA software version 15. Chi-square test and multiple logistic regression were conducted on all independent variables and statistical significance was accepted at p < 0.05. The study identified the following as the most perceived frequently disposed nonfaecal matter into FS: sanitary pads and diapers (38.5%), fabrics/rags (23.2%), toilet rolls (20.8%), razor/shaving sticks (10.3%), and others (7.2%). Gender, state of toilet facility (roof or unroofed), presence of container for collecting other types of waste in the toilet room, and state of container in toilet room either covered or uncovered were the factors found to be significantly associated with the disposal of solid waste (SW) into FS at 95% confidence level. The fear of exposing used sanitary materials for rituals, the use of fabric as an alternative to toilet rolls, and the desire to conceal aborted pregnancies from the public were some of the reasons alluded to the disposal acts. Education and awareness campaigns on proper SW disposal practices, appropriate use of toilet facilities, and the resource potentials of FS were found to be the best way forward to discourage indiscriminate disposal of SW into FS. [ABSTRACT FROM AUTHOR]

Discrete count time series data with an excessive number of zeros have warranted the development of zero-inflated time series models to incorporate the inflation of zeros and the overdispersion that comes with it. In this paper, we investigated the characteristics of the trend of daily count of COVID-19 deaths in Ghana using zero-inflated models. We envisaged that the trend of COVID-19 deaths per day in Ghana portrays a general increase from the onset of the pandemic in the country to about day 160 after which there is a general decrease onward. We fitted a zero-inflated Poisson autoregressive model and zero-inflated negative binomial autoregressive model to the data in the partial-likelihood framework. The zero-inflated negative binomial autoregressive model outperformed the zero-inflated Poisson autoregressive model. On the other hand, the dynamic zero-inflated Poisson autoregressive model performed better than the dynamic negative binomial autoregressive model. The predicted new death based on the zero-inflated negative binomial autoregressive model indicated that Ghana's COVID-19 death per day will rise sharply few days after 30th November 2020 and drastically fall just as in the observed data. [ABSTRACT FROM AUTHOR]