RESUMO
BACKGROUND: The declaration of COVID-19 as a pandemic on March 11 2020, by the World Health Organisation prompted the need for a sustained and a rapid international response. In a swift response, the Government of Ghana, in partnership with Zipline company, launched the use of Unmanned Automated Vehicles (UAV) to transport suspected samples from selected districts to two foremost testing centres in the country. Here, we present the experiences of employing this technology and its impact on the transport time to the second largest testing centre, the Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR) in Kumasi, Ghana. METHODS: Swab samples collected from suspected COVID-19 patients were transported to the Zipline office by health workers. Information on the samples were sent to laboratory personnel located at KCCR through a WhatsApp platform to get them ready to receive the suspected COVID-19 samples while Zipline repackaged samples and transported them via drone. Time of take-off was reported as well as time of drop-off. RESULTS: A total of 2537 COVID-19 suspected samples were received via drone transport from 10 districts between April 2020 to June 2021 in 440 deliveries. Ejura-Sekyedumase District Health Directorate delivered the highest number of samples (765; 30%). The farthest district to use the drone was Pru East, located 270 km away from KCCR in Kumasi and 173 km to the Zipline office in Mampong. Here, significantly, it took on the average 39 minutes for drones to deliver samples compared to 117 minutes spent in transporting samples by road (p<0.001). CONCLUSION: The use of drones for sample transport during the COVID-19 pandemic significantly reduced the travel time taken for samples to be transported by road to the testing site. This has enhanced innovative measures to fight the pandemic using technology.
Assuntos
COVID-19 , Dispositivos Aéreos não Tripulados , Humanos , Gana , PandemiasRESUMO
Objectives: To investigate factors contributing to neonatal admission outcomes at Effia Nkwanta Regional Hospital (ENRH) Method: All neonatal admissions to the Neonatal & Intensive Care Unit (NICU) of the hospital that were entered into the DHIMS2 database were extracted and complemented with additional information from patients' folder review. The data from the two sources were merged and analysed using SPSS version 21. Univariate and multivariate regression analysis was performed to identify factors associated with admission outcomes, taking statistical significance as p < 0.05. ARC-GIS version 10.1 was used to describe the geospatial distribution of health facilities referring to ENRH. Setting: Neonatal & Intensive Care Unit of ENRH Participants: All neonates admitted to NICU between January and December 2015. Intervention: None Results: Nine Hundred and Ninety-Three out of the 1150 neonatal admissions were entered into DHIMS2. Fifty-two percent were males, 57.3% were delivered through Caesarean Section, 72% were admitted within 2 days of birth, and 56.8% had normal birth weight. FiftyEight percent of the neonates were delivered at the ENRH, whilst 39.9% were referred from health facilities located within Sekondi-Takoradi Metropolis. At 1 minute, only 14% of the neonates had normal Apgar score (8-10), and this improved to 50% at 5 minutes. The main causes of neonatal admission were birth asphyxia 21.0%, followed by prematurity 17.5%, neonatal jaundice 17.1% and neonatal sepsis 14.5%. The death rate was 18% with more than 80% of the deaths occurring during the early neonatal period. More than 80% of deaths were due to four admission diagnoses: birth asphyxia, prematurity, neonatal jaundice, neonatal sepsis. Factors associated with adverse admission outcome are: low birth weight, delivery by Caesarean Section and low Apgar score at 5 minutes. Conclusions: The institution of appropriate interventions to reduce or manage the four major causes of adverse neonatal admission outcomes will significantly reduce neonatal mortality in the hospital