Household-Reported Availability of Drinking Water in Africa: A Systematic Review

Domestic drinking water supplies prone to interruptions and low per capita domestic water availability have been frequently reported among African households. Despite expanded international monitoring indicators that now include metrics of water availability, the range of methods used for measuring and monitoring availability remains unclear in Africa. Few household surveys have historically assessed water continuity and per capita availability, and both pose measurement challenges. This paper aims to examine the methods used to measure availability and synthesise evidence on African domestic water availability by systematically reviewing the literature from 2000–2019. Structured searches were conducted in five databases: Web of Science Core Collection, Scopus, GEOBASE, Compendex and PubMed/Medline. A total of 47 of 2406 reports met all inclusion criteria. Included studies were based on empirical research which reported the household’s perspective on a water availability measure. Most studies had methodological problems such as small sample sizes, non-representative sampling and incomplete reporting of methods and measures of uncertainty. Measurement of drinking water availability is primarily reliant on quantifying litres/capita/day (LPCD). Only four (9%) of the included studies reported an average water availability over the international benchmark of 50 LPCD. This pattern of water insufficiency is broadly consistent with previous studies of domestic water availability in Africa. The review highlights the need for high-quality and representative studies to better understand the uncertainties and differences in household water availability across Africa, and the methods used to measure it.

A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems

In this work it is proposed a model for the assessment of availability measure of fault tolerant systems based on the integration of continuous time semi-Markov processes and Bayesian belief networks. This integration results in a hybrid stochastic model that is able to represent the dynamic characteristics of a system as well as to deal with cause-effect relationships among external factors such as environmental and operational conditions. The hybrid model also allows for uncertainty propagation on the system availability. It is also proposed a numerical procedure for the solution of the state probability equations of semi-Markov processes described in terms of transition rates. The numerical procedure is based on the application of Laplace transforms that are inverted by the Gauss quadrature method known as Gauss Legendre. The hybrid model and numerical procedure are illustrated by means of an example of application in the context of fault tolerant systems.