Department of Environmental Health Sciences
Permanent URI for this collectionhttps://dspace.njala.edu.sl/handle/20.500.144402/168
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Item Regression Modelling and Analysis of Cell phone-Based Syndromic Surveillance Data for Ebola in Sierra Leone(OMICS Publishing Group, 2016) Kangbai, Jia Bainga**Aim:** To determine the out degree centrality for multivariate analysis, examine the demographic differences and characteristics of callers who make more calls, and determine callers who are more likely to make at least one positive Ebola call.Methods: Surveillance data for 393 suspected Ebola cases (192 males, 201 females) were collected from October 23, 2014 to June 28, 2015 using cell phone technology.UCINET and Net Draw software were used to determine the out degree centrality used for multivariate analysis.Poisson and logistic regression analyses were used to do multivariable analysis.Result: Women (AOR=0.33,95% CI \[0.14, 0.81\]) was associated with decreased odds of making at least one positive Ebola surveillance call compared to men.Women (IR= 0.63, 95% CI \[0.49, 0.82\]) was also associated with making fewer Ebola surveillance calls compared to men. **Conclusion:** This study shows that the combination of cell phone technology with user-friendly and open-source social network software such as UCINET and Net draw will provide an important adjunct to the traditional measures of epidemiologic surveillance.Item Health Care Facility Network Efficiency and Location Crucial for Ebola Treatment Outcome(OMICS Publishing Group, 2018) Kangbai, Jia Bainga**Background:** The application of network analysis in public health research is gaining popularity with the belief that health problems are a product of complex social, political and economic causes.Organisational networks can be used in public health to design and evaluate public health programs.There have been multiple studies in the past relating to public health organisations and HIV/AIDS using organisational networking method.Here we use social network analysis to analyse the association between the network positions of health care facilities and the treatment outcome of Ebola patients from these health care facilities in Sierra Leone. **Methods:** We extracted and later analysed treatment outcome data obtained from the Case Report Forms (CRF) of 117 Ebola patients who sought Ebola treatment at the Kenema Government Hospital from June 2014 to April 2015.For ego network purpose, we considered each Ebola referral health care facility as an ego.Poisson regression analysis was used to determine the association between Ebola mortality rates in a health care facility and the ego's structural holes.Results: The median age, length of stay during Ebola treatment, and the period it takes an Ebola patient to survive treatment following from onset of signs and symptoms were 20 (IQR=17.5 years), 15 (IQR=11 days) and 7 (IQR=5.3days) respectively.There were differences in ego, network efficiency, effective size and constraint for the factors associated with mortality rates for Ebola patients treated at the Kenema Government Hospital.Conclusion: Establishing non-redundant contacts within a health care facility network and expanding their locations can reduce Ebola mortality rates during outbreak.Item Epidemiological characteristics, clinical manifestations, and treatment outcome of 139 paediatric Ebola patients treated at a Sierra Leone Ebola treatment center(BioMed Central, 2019-01-24) Kangbai, Jia BaingaBACKGROUND: The West Africa Ebola Virus Disease (EVD) outbreak in 2014-2016 was declared by the World Health Organization (WHO) a public health emergency of international concern. Most of the previous studies done in Sierra Leone relating to the clinical and epidemiological features of EVD during the 2014-2016 West African outbreak focused on adult EVD patients. There have been conflicting reports about the effects of EVD on children during previous outbreaks. METHODS: This is an observational retrospective analysis of medical data of all laboratory confirmed paediatric EVD patients below 15 years of age who were admitted at the 34 Military Hospital Ebola Treatment Center (ETC) in Wilberforce, Sierra Leone between June 2014 to April 2015. We analyzed the sociodemographic and clinical characteristics of paediatric EVD cases contained in case report forms that were collected by Ebola surveillance officers and clinicians at the 34 Military Hospital ETC. Both univariate and multivariate logistic regression models were used to determine the sociodemographic and clinical characteristics of paediatric EVD patients that were associated with EVD facility-based mortality. RESULTS: The majority of the paediatric EVD cases in this study were female (56.1%), pupils (51.1%), and 43.2% belonged to the age group between 10 years and below 15 years. The median age of the paediatric EVD cases was 9 years (interquartile range = 4 to 11 years). Adjusting for other covariates in the model, male paediatric EVD patient (AOR = 13.4, 95% CI = \[2.07-156-18\], p < 0.05), EVD patient with abdominal pain (AOR = 11.0, 95% CI = \[1.30-161.81\], p < 0.05), vomiting (AOR = 35.7, 95% CI = \[3.43-833.73\], p < 0.05), signs of conjunctivitis (AOR = 17.4, 95% CI = \[1.53-342.21\], p < 0.05) and difficulty in breathing (AOR = 23.3, 95% CI = \[1.92-713.01\], p < 0.05) at the time of admission had increased odds of dying during EVD treatment. CONCLUSIONS: We recommend the adoption of case definitions currently in vigour to cater for specific characteristics of paediatric patients. Subgroups that can be identified by applying the model developed in this study may require special attention and intensified care.Item Severity score for predicting in-facility Ebola treatment outcome(Elsevier BV, 2020-08-04) Kangbai, Jia BaingaPurpose Sierra Leone recorded the highest incidence rate for the 2013-2016 West African Ebola outbreak. In this investigation, we used the medical records of Ebola patients with different sociodemographic and clinical features to determine the factors that are associated with Ebola treatment outcome during the 2013-2016 West African Ebola outbreak in Sierra Leone and constructed a predictive in-facility mortality score. Methods We used the anonymized medical records of 1077 laboratory-confirmed pediatric and adult patients with EVD who received treatment at the 34 Military Hospital and the Police Training School Ebola Treatment Centers in Sierra Leone between the period of June 2014 and April 2015. We later determined the in-facility case fatality rates for Ebola, the odds of dying during Ebola treatment, and later constructed a predictive in-facility mortality score for these patients based on their clinical and sociodemographic characteristics. Results We constructed a model that partitioned the study population into three mortality risk groups of equal patient numbers, based on risk scoring: low (score ≤ -5), medium (score -4 to 1), and high-risk group (score ≥ 2). The CFR of patients with EVD belonging to the low- (≤-5), medium (-4 to 1), and high- (≥2) risk groups were 0.56%, 9.75%, and 67.41%, respectively. Conclusions We succeeded in designing an in-facility mortality risk score that reflects EVD clinical severity and can assist in the clinical prioritization of patients with EVD.Item Re-reading ACT, BCG, and Low COVID-19 in Africa(Springer Nature, 2021) Kangbai, Jia BaingaOctober 11, 2020, marks the seventh month since the World Health Organization (WHO) officially declared COVID-19 a pandemic. Unlike other coronavirus diseases, there is a geographically disproportionate distribution of the incidence of COVID-19 cases around the world. We observed a significantly high COVID-19 cases and deaths in countries and territories with no or very small number of malaria cases or no or low national TB cases in 2018. We speculate that the high incidence of COVID-19 cases and deaths in countries less affected by malaria is partly due to overexposure to malaria which led to the regular use of the artemisinin anti-malaria drugs as well as the regular use of bacillus Calmette-Guérin (BCG) vaccine for TB prevention. The vaccine produced an almost life-long immunity to TB and meningitis to its recipients. We are thus calling for a COVID-19 containment and clinical management protocol that will incorporate the use of the anti-malaria ACT drug cocktail and BCG vaccine on compassionate ground.Item Africa’s COVID-19 third wave: A coupled behavior-disease system in a mutual feedback loop(2021-10-30) Kangbai, Jia BaingaA year after COVID-19 was declared a pandemic much of the Africa continent started experiencing spikes in the number of COVID-19 cases and related deaths in what was referred to as the third wave of the pandemic. These spikes came right behind the heels of a second wave of the pandemic that barely went unnoticed in Africa. As of July 2021, Morocco, South Africa, Tunisia, Egypt, Nigeria, Libya, Kenya, Algeria, Zambia and Ethiopia accounted for approximately 86% of the reported increase in COVID-19; these countries were aptly described as being at the forefront of the continent’s third wave of the COVID-19 pandemic. Unlike those countries in Asia and Latin America that experienced what may generally being described as autochthonous COVID-19 third wave, Africa’s third wave COVID-19 cases are widely believed to have been triggered by imported cases. Africa like the rest of the world relaxed its COVID-19 restrictions almost at the same time; hence the continent’s spikes of COVID-19 cases and related deaths during the third wave of the pandemic have raised some questions.