N'zerekore is a geographical region of Guinea, which houses a weather observatory located at longitude 8.8°, latitude 7.7° and altitude 475 m. This region is of major socio-economic interest for the country. The climatological study of this region shows the variability of each parameter. The objective of this study was to analyze meteorological parameters trends and to assess the space-time evolution of some agro-climatic risks related to the main trends observed in the meteorological parameters regime of this region. In this study, programming tools were used for processing and analyzing meteorological parameters data, including temperatures, rains, wind, evaporation and storms measured in this observatory from 1931 to 2014. The interannual, annual and daily variations of these parameters were obtained, as well as temperature, precipitation anomalies and agroclimatic indexes trends. The analyzing of these variations explained that September is the rainiest months, and the year 1932, 1957 and 1970 are normal, rainy and dry year, respectively. The evaporation increased since 1971 from January to March and November to December. A positive temperature anomaly was observed since 1973 with the maximum 26-33 °C and the minimum 16-21 °C. A dominant westerly wind with a speed of 2.6 m/s was determined. Agro-climatic parameters in N'zerekore have high variability. From 1931 to 2014, three major periods can be distinguished: a wet period from 1931 to 1977, a dry period from 1978 to 1994 and rainfall variability from 1995 to 2014. The trend of these parameters explains the impact of climate change in this part of the world. This is exacerbated by human activity (deforestation), thus mitigation measures are necessary. It would be useful to extend this study throughout the country.
Three outbreaks occurred in the last five years and it was observed that mortality was often confined to the initial half of the outbreak period and healthcare personnel were the major patients in the first half. Between 2009 and 2019, the monthly incidence ranged between 0 and 14.5 per 100,000 population. Univariate negative binomial regression analysis of the influenza incidence with the local weather parameters demonstrated that absolute humidity, relative humidity, insolation and rainfall were associated. On multivariate regression analysis, absolute humidity (IRR: 1.37, 95%
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