Determination of Monthly Effect on fire Outbreaks: Case Study: Ashanti Region, Ghana.

The occurrences of Fire Outbreaks and cost of damages are of an increasing trend globally for the past decade. There is no day without incidence of fire in some part of Ghana which affect individual citizens and the government economically. The study was based on monthly time series data on Fire Outbreaks and obtained from Ghana’s Ashanti Regional Fire Service database. Multiple Regression was employed to determine the monthly fire effects by considering differential effects in terms of change in percentage. However, the study revealed that there is no serial correlation of the in the model residuals with Durbin-Watson statistic of 2.011460 and also F-statistic of 9.651750 and pvalue of 0.0000 indicated that, the regression model was significant. The findings have revealed that, the month of January showed the highest increment of 72% and this can be attributed to the dry weather conditions corresponding to the harmattan season. Relatively, the month of April revealed the highest percentage decrement of 30% on Outbreak of and this could be due to continuous rain fall during that time. However, the study recommends that, fire stakeholders such as Ghana National Fire Service, Ghana police Service, insurance companies and other financial stakeholders should come together educate, implement regularizations and policies measures during the harmattan and cultivation seasons to reduce the number of fire outbreaks in the country. Furthermore, with developing effective means of managing fire, it is recommended that they make data on daily, weekly and monthly number of Fire occurrences readily available to researchers. This would enable researchers to investigate within the month effects on the number of fire outbreaks. This would enable researchers to investigate within the month effects on the number of fire outbreaks.\

Keywords: Multiple regression Model, Fire Outbreak, Ashanti Region and Monthly Effects.