The quality of water served in the Orotta National Referral Hospital

Background: The principal risks to human health associated with the consumption of unsafe drinking water are microbiological. According to the WHO and UNICEF report 2.6 billion people do not have access to good quality of water. About 1.1 billion people globally do not have access. About 2 million people mostly of less than 5 years children also die as a result of diarrheal diseases related to consumption of water that is microbiologically contaminated. Objective: The objective of this study was to measure the quality of water served to the different sections of Orotta National Referral Hospital using WHO protocols. Methods: Water samples were collected from different sources in the National Referral Orotta Hospital compound according to the WHO guidelines and the multi-tube method or most probable number method was used for the microbiological count. Results: The findings from the study showed that some of the samples of water from National Referral Pediatric Hospital, and National Medical and Surgical Referral Hospital reservoirs did not meet some of the WHO guidelines for safe drinking water. Conclusion and recommendations: The water contamination emanated from the reservoirs of the Orotta Hospital, because the samples taken as a control from outside the Hospital compound were free of contamination. Water reservoirs should be washed on regular basis. Chlorination and other treatment modalities for the water in the reservoir should also be considered and applied. Water quality surveillance should be done several times in a year not only just once

Spatiotemporal variability of rainfall trends and influencing factors in Rwanda

Rainfall is the most important meteorological variable that influences the economic development of Rwanda. Changes in rainfall trends and variability over recent past years have become a great concern to policymakers and scientists. This study aims at examining the spatiotemporal variability of rainfall over Rwanda and the teleconnections of rainfall with different large-scale ocean-atmospheric variables at different timescales. The study used rainfall data of Climate Hazards Category Infrared Precipitation with Stations (CHIRPS) and Climate Research Unit Time Series Version 4 (CRU) for the period 1981–2017. Several statistical methods, including standardized anomaly, Empirical Orthogonal Functions (EOF), Pearson Correlation, Mann-Kendall (MK), and Sen's gradient estimator, were used to assess the variability, trends, and teleconnections of rainfall with various driving factors. Results revealed a bimodal rainfall pattern in its annual cycle. The spatial distribution of annual and seasonal rainfall showed a southwest to northwest rainfall gradient. The MK test revealed a decreasing trend in annual rainfall in the southwest part of the country. Overall, March to May (MAM) rainy seasons showed a decreasing and September to December (SOND) rainy season an increasing trend over Rwanda. The EOF analysis revealed that the leading mode of variability for MAM rainfall parades a unimodal scheme with negative loadings that can explain 59.3% of the total rainfall variance. The dominant mode of variability of SOND rainfall revealed the same pattern but with positive loadings that can explain 58.1% of the total variance. Spatial correlation showed that the MAM (SOND) rainfall has a weak (strong) relationship with the Indian Ocean sea surface temperature (SST), which means a negative (positive) Indian Ocean Dipole can lead to anomalously wet (dry) conditions over Rwanda. A stronger influence of El-Nino Southern Oscillation (ENSO) on SOND rainfall than MAM rain was noticed. The results of this study are crucial in developing appropriate mitigation measures to curb the impacts of climate change on the agriculture and water resources of Rwanda