This study reviewed the design and deployment of relational geodatabase on mobile GIS application, using collector for ArcGIS and survey 123 for ArcGIS platforms for COVID-19 contact tracing in Ghana during the lockdown. The study assessed whether cases spread by physical neighborhood contacts, defined by a 2km buffer of initial known 60 cases location. The application was deployed on the android tablet, which was used by field workers. Application Post-deployment review shows that from 30th March to 4th April 2020, 828 samples were collected with 34 confirmed cases, of which 61% occurred outside the 2km buffer. From 1-30 April 2020, 8,748 individuals with 16,087 contacts were tested within the physical neighbourhoods, 2.4% turned positive. Similarly, 7,501 individuals with 17,071 contacts were tested outside the physical neighbourhoods with 4.3% positives. Results suggest that more infections occurred outside the case’s physical neighbourhoods possibly due to; (1) existence of unknown cases prior to lockdown; (2) cases were moving outside their physical neighborhood and infecting others; (3) panic movements of cases within the 3 days window between announcement and enforcement of lockdown; (4) movement of cases into the country through unapproved routes. New cases were identified outside the lockdown areas, which could not be explained. This study raises questions about (1) the understanding of the mode of spread of the virus (2) the implementation of the lockdown, including the geographic coverage and timing. It is recommended that future decisions on contact tracing and lockdown should be guided by an understanding of the disease geography.
Objective: We describe the use of integrated geospatial applications for the provision of access to timely and accurate data on samples, visualisation of Spatio-temporal patterns of cases and effective communication between field sample collectors, testing laboratories, Regional Health directors and Government Decision Makers.Design: This study describes how an integrated geospatial platform based on case location and intelligence was developed and used for effective COVID-19 response during the initial stages of COVID-19 in Ghana.Data Source: Collector for ArcGIS, ArcGIS Survey123Main outcome measure: successful development and deployment of integrated geospatial applications and analytics. Results: The Collector for ArcGIS app was customised to collect COVID-19 positive cases location information. Survey 123 was introduced as a COVID-19 contact tracing application to digitise the case-based forms and provide real-time results from the laboratories to GHS and other stakeholders. The laboratory backend allowed the testing laboratories access to specific information about each patient (sample) collected by the fieldworkers. The regional supervisors’ backend web application provided accessing test results for confidentiality and timely communication of results.Conclusion: Geospatial platforms were successfully established in Ghana to provide timely results to Regional Health Directors and Government decision-makers. This helped to improve the timeliness of response and contact tracing at the district level.
In Ghana, maize (Zea mays) is a crop crucial to achieving food and nutrition security. Maize consumption has increased exponentially over the past decades and contributes to 25% of the caloric consumption in the country. In order to assist in decision-making and guide investment in sustainable intensification of maize production, this study set out to identify the determinants of yield and to arrive at potential interventions for closing the maize yield gap. These were quantified using analytical approaches that combine a light use efficiency crop model (LINTUL-1) with statistical and geospatial analyses. Legacy data, auxiliary covariables, and maize fertilizer trials on eight experimental stations in Ghana were used in this study. Overall, the maize yield gap across the stations and trial treatments ranged from 17% to 98%. The variation in yield gap within a single station indicates a significant scope for closing the yield gap through site-specific nutrient management. Multiple linear regression models that explained 81% of the variability in maize yield gap identified soil organic matter, soil water-holding capacity, root zone depth, rainfall, sulfur fertilizer, and nitrogen fertilizer, in that order of importance, as the major determinants for closing the yield gap in the major agroecological zones of Ghana. The yield gap decreased by 1.4 t ha-1 with a 1% increase in soil organic matter. A 1 mm increase of the soil water-holding capacity reduced the yield gap by 1.06 t ha-1, while an increase in pH and in the application of potassium fertilizer widened the gap. These results suggest that both soil physical and chemical properties, together with weather data, should be taken into consideration to arrive at site-specific fertilizer recommendation and other agronomic practices.
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