This paper focuses on time series forecasting of monthly occurrence of fatal road accidents in Ondo State of Nigeria. Its aim, however, is to use time series analysis to analyze the data obtained from Federal Road Saf...This paper focuses on time series forecasting of monthly occurrence of fatal road accidents in Ondo State of Nigeria. Its aim, however, is to use time series analysis to analyze the data obtained from Federal Road Safety Corps （FRSC）, Ondo State Command; which was considered in two cases： the total cases reported （TCR） and the number of deaths resulted from accidents （NOD）. Various smoothing models for time series were used to analyze the two cases. Based on the models, predictions were made and the results show a steady increase as a result of long-term effects on road accidents for the two cases. It was found also that simple exponential smoothing model is the appropriate model for both TCR and NOD.展开更多
This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state fo...This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state for the period from 1998 to 2008. In addition, sea surface temperatures （SSTs） over equatorial Pacific Ocean were integrated in the analysis. The association between each of the meteorological-biometeorological parameters and clinical-reported malaria cases was examined by using Poisson distribution and log as link function between the two categories of dataset. The next step was the building of a model by using Poisson multiple regression models （GLMs） in order to know the weather variables that lead to statistically changes in clinical-reported malaria cases. The study revealed that an increase of I m.s1 of wind speed can lead to an increase of about 164% and 171% in the monthly occurrence of malaria at 95% confidence interval in derived savanna and humid forest zone respectively. Also, an increase of I ℃ in air temperature and sea surface temperature is associated with 53.4% and 29% increase in monthly malaria occurrence （CI： 95%） in derived savanna while an increase of 1 ℃ in air temperature and sea surface temperature is associated with 56.4% and 15.4% increase in monthly malaria occurrence at 95% confidence interval in humid forest zone of Ondo State展开更多
Introduction: Annual outbreak of Lassa Fever (LF) has been reported in Ondo State over the years. We analyzed LF surveillance data from January 2014 to December 2019 to describe the epidemiological pattern of the outb...Introduction: Annual outbreak of Lassa Fever (LF) has been reported in Ondo State over the years. We analyzed LF surveillance data from January 2014 to December 2019 to describe the epidemiological pattern of the outbreak. Method: Lassa fever dataset from January 2014 to December 2019 was obtained from the State Ministry of Health. Variables analyzed include date of onset of symptom, age, gender, place (Local Government Area, LGA) and outcome of laboratory test. Data were summarized using frequencies, proportions, chart and maps. Results: From January 2014 and December 2019, 2141 suspected LF cases were reported. Of these, 551 cases were laboratory confirmed with 134 deaths recorded. The LF cases (suspected vs. confirmed) reported increased in 2016 (73 vs. 19), 2017 (207 vs. 76), 2018 (452 vs. 159) and 2019 (856 vs. 285) respectively. Most of the confirmed cases (89.5%) were ≥15 years while more than half (53.7%) were males. Prior to 2016, only two LGAs (Owo and Ose) recorded continued transmission of the disease. However, between 2016 and 2019, the disease had spread to 8 neighboring LGAs (P < 0.001) with the CFR declining from 67% in 2015 to 20% in 2019. Conclusion: We found an unusual increase in the suspected LF cases reported between January 2016 and December 2019 with a corresponding increase in the confirmed cases and high annual case fatality rates. Hence, we recommend intensified surveillance activities to enhance timely reporting of cases and laboratory confirmation to ensure early commencement of treatment to reduce the case fatality rate.展开更多
<span style="font-family:Verdana;"><strong>Background: </strong>On 3<span style="white-space:nowrap;"><sup>rd</sup></span> April 2020, an outbreak of Coron...<span style="font-family:Verdana;"><strong>Background: </strong>On 3<span style="white-space:nowrap;"><sup>rd</sup></span> April 2020, an outbreak of Coronavirus disease-2019 (COVID-19) was confirmed in Ondo State, Southwest Nigeria. Field investigations were conducted by the State Ministry of Health (MoH) to identify and confirm additional cases. This paper provides the outcome of the epidemiological investigation of the outbreak to further guide outbreak response activities. <strong>Methods:</strong> Field epidemiology methods coordinated by the State Public Health Emergency Operations Center (PHEOC) were used in the outbreak investigation. Suspected cases were reported through the routine Integrated Disease Surveillance and Response (IDSR) network in the State. Also, active case search/finding to communities and health facilities using the operational case definitions was conducted. Furthermore, the state COVID-19 emergency call center was established with toll-free phone number provided to members of the public to call-in to report suspected persons with symptoms consistent with the COVID-19 operational case definition (signal). All cases reported were investigated with nasopharyngeal sample collected and confirmatory testing for COVID-19 done by real-time polymerase chain reaction (RT-PCR) in a national reference laboratory. Information of each case investigated was documented using the COVID-19 case investigation form and COVID-19 line-list which captured socio-demographic characteristics, history of exposure to COVID-19, presenting symptoms, travel history and sample collection details. Data were extracted from the case investigation form and line list and analyzed using SPSS version 20, with a p-value set at < 0.05. <strong>Results:</strong> A total of 4353 suspected cases were reported and investigated, of which 1316 cases were confirmed between March 19, 2020 and August 9, 2020. The mean age of the confirmed cases was 37.8 ± 14.8 years. The highest proportion of COVID-19 cases and deaths occurred in the age group 20 - 39 years (50.6%) and ≥60 years (13.5%), respectively. More males (52.4%) were affected than females (45.8%). There were 404 (30.7%) healthcare workers infection. About a quarter (325;24.7%) of the cases was symptomatic and presented with key symptoms such as cough (98/325;30.2%) and fever (74/325;22.8%) during the investigation. A case fatality rate (CFR) of 2.2% was recorded in 7 of the 17 Local Government Areas (LGAs) where confirmed cases were reported in the State. Most of the confirmed cases, 1169 (88.8%) reside in urban LGAs of the State. The epidemic curve shows a propagated pattern of transmission with the outbreak reaching its peak on July 2, 2020. Significantly, higher proportion of death was recorded in the age group ≥ 60 years (14;13.5%) and among males (26;3.6%) (p < 0.001). <strong>Conclusions:</strong> Our investigation found high transmission of COVID-19 infection among urban residents (LGAs) and health care workers with high mortality among males in older age group in the State. Hence, we recommend intensified risk communication and use of community structures to ensure compliance with public health COVID-19 preventive protocols including enforcing infection prevention and control compliance, particularly among high-risk groups.</span>展开更多
文摘This paper focuses on time series forecasting of monthly occurrence of fatal road accidents in Ondo State of Nigeria. Its aim, however, is to use time series analysis to analyze the data obtained from Federal Road Safety Corps （FRSC）, Ondo State Command; which was considered in two cases： the total cases reported （TCR） and the number of deaths resulted from accidents （NOD）. Various smoothing models for time series were used to analyze the two cases. Based on the models, predictions were made and the results show a steady increase as a result of long-term effects on road accidents for the two cases. It was found also that simple exponential smoothing model is the appropriate model for both TCR and NOD.
文摘This study focuses on the influence of weather and climate on malaria occurrence based on human-biometeorological methods was carried out in Ondo State, Nigeria using meteorological and malaria dataset in the state for the period from 1998 to 2008. In addition, sea surface temperatures （SSTs） over equatorial Pacific Ocean were integrated in the analysis. The association between each of the meteorological-biometeorological parameters and clinical-reported malaria cases was examined by using Poisson distribution and log as link function between the two categories of dataset. The next step was the building of a model by using Poisson multiple regression models （GLMs） in order to know the weather variables that lead to statistically changes in clinical-reported malaria cases. The study revealed that an increase of I m.s1 of wind speed can lead to an increase of about 164% and 171% in the monthly occurrence of malaria at 95% confidence interval in derived savanna and humid forest zone respectively. Also, an increase of I ℃ in air temperature and sea surface temperature is associated with 53.4% and 29% increase in monthly malaria occurrence （CI： 95%） in derived savanna while an increase of 1 ℃ in air temperature and sea surface temperature is associated with 56.4% and 15.4% increase in monthly malaria occurrence at 95% confidence interval in humid forest zone of Ondo State
文摘Introduction: Annual outbreak of Lassa Fever (LF) has been reported in Ondo State over the years. We analyzed LF surveillance data from January 2014 to December 2019 to describe the epidemiological pattern of the outbreak. Method: Lassa fever dataset from January 2014 to December 2019 was obtained from the State Ministry of Health. Variables analyzed include date of onset of symptom, age, gender, place (Local Government Area, LGA) and outcome of laboratory test. Data were summarized using frequencies, proportions, chart and maps. Results: From January 2014 and December 2019, 2141 suspected LF cases were reported. Of these, 551 cases were laboratory confirmed with 134 deaths recorded. The LF cases (suspected vs. confirmed) reported increased in 2016 (73 vs. 19), 2017 (207 vs. 76), 2018 (452 vs. 159) and 2019 (856 vs. 285) respectively. Most of the confirmed cases (89.5%) were ≥15 years while more than half (53.7%) were males. Prior to 2016, only two LGAs (Owo and Ose) recorded continued transmission of the disease. However, between 2016 and 2019, the disease had spread to 8 neighboring LGAs (P < 0.001) with the CFR declining from 67% in 2015 to 20% in 2019. Conclusion: We found an unusual increase in the suspected LF cases reported between January 2016 and December 2019 with a corresponding increase in the confirmed cases and high annual case fatality rates. Hence, we recommend intensified surveillance activities to enhance timely reporting of cases and laboratory confirmation to ensure early commencement of treatment to reduce the case fatality rate.
文摘<span style="font-family:Verdana;"><strong>Background: </strong>On 3<span style="white-space:nowrap;"><sup>rd</sup></span> April 2020, an outbreak of Coronavirus disease-2019 (COVID-19) was confirmed in Ondo State, Southwest Nigeria. Field investigations were conducted by the State Ministry of Health (MoH) to identify and confirm additional cases. This paper provides the outcome of the epidemiological investigation of the outbreak to further guide outbreak response activities. <strong>Methods:</strong> Field epidemiology methods coordinated by the State Public Health Emergency Operations Center (PHEOC) were used in the outbreak investigation. Suspected cases were reported through the routine Integrated Disease Surveillance and Response (IDSR) network in the State. Also, active case search/finding to communities and health facilities using the operational case definitions was conducted. Furthermore, the state COVID-19 emergency call center was established with toll-free phone number provided to members of the public to call-in to report suspected persons with symptoms consistent with the COVID-19 operational case definition (signal). All cases reported were investigated with nasopharyngeal sample collected and confirmatory testing for COVID-19 done by real-time polymerase chain reaction (RT-PCR) in a national reference laboratory. Information of each case investigated was documented using the COVID-19 case investigation form and COVID-19 line-list which captured socio-demographic characteristics, history of exposure to COVID-19, presenting symptoms, travel history and sample collection details. Data were extracted from the case investigation form and line list and analyzed using SPSS version 20, with a p-value set at < 0.05. <strong>Results:</strong> A total of 4353 suspected cases were reported and investigated, of which 1316 cases were confirmed between March 19, 2020 and August 9, 2020. The mean age of the confirmed cases was 37.8 ± 14.8 years. The highest proportion of COVID-19 cases and deaths occurred in the age group 20 - 39 years (50.6%) and ≥60 years (13.5%), respectively. More males (52.4%) were affected than females (45.8%). There were 404 (30.7%) healthcare workers infection. About a quarter (325;24.7%) of the cases was symptomatic and presented with key symptoms such as cough (98/325;30.2%) and fever (74/325;22.8%) during the investigation. A case fatality rate (CFR) of 2.2% was recorded in 7 of the 17 Local Government Areas (LGAs) where confirmed cases were reported in the State. Most of the confirmed cases, 1169 (88.8%) reside in urban LGAs of the State. The epidemic curve shows a propagated pattern of transmission with the outbreak reaching its peak on July 2, 2020. Significantly, higher proportion of death was recorded in the age group ≥ 60 years (14;13.5%) and among males (26;3.6%) (p < 0.001). <strong>Conclusions:</strong> Our investigation found high transmission of COVID-19 infection among urban residents (LGAs) and health care workers with high mortality among males in older age group in the State. Hence, we recommend intensified risk communication and use of community structures to ensure compliance with public health COVID-19 preventive protocols including enforcing infection prevention and control compliance, particularly among high-risk groups.</span>
