A Review of Published Studies Looking At Statistical Models And Methods And Their Application To Problems Of Infectious

1. A REVIEW OF PUBLISHED STUDIES LOOKING AT STATISTICAL MODELS ANDMETHODSAND THEIR APPLICATION TO PROBLEMS OF INFECTIOUS DISEASES SUCH AS COVID-19INBMJ AnAcademicpresentationby Dr.NancyAgnes,Head,TechnicalOperations,Statswork Group www.statswork.com Email:info@statswork.com

2. Introduction Statisticalmodelsinhumanhealthscience Factoranalysis Bayesianmeta-analysis Modelstoforecasttheriskofcovid-19inthegeneralpopulation Diagnostic models to discover covid-19 in patients with suspectedinfection Predictivemodelstodiagnosecovid-19 Conclusion Outline TODAY'SDISCUSSION

3. INTRODUCTION Health science research is the most interesting research area as we identify the pattern of Genomic diseases and variousother kindsofdiseases.

4. Themostcommonstatisticalapproachforany human health studies is correlation and regression analysis. STATISTICAL MODELS IN HUMANHEALTH SCIENCE Suppose, consider a vaccine effectiveness study, andtheresearcherwantstoidentifythe effectiveness of vaccine among the gender or age category. The correlation technique will be useful to identify therelationshipbetweenthesetwovariables. Contd...

5. Andsupposetheresearcherwantstopredicttheeffectivenessoffutureoutcomes.Andsupposetheresearcherwantstopredicttheeffectivenessoffutureoutcomes. Inthatcase,theregressionanalysiswillbeusefulasitidentifiestheaveragelinear relationshipbetween thedependent andindependentvariables. Apart from the usual correlation and regression analysis, many researchers adopt dimensionalityreduction techniquessuch asfactor analysis.

6. Factor analysis reduces the dimensions and creates the latent variables.Eachlatentvariableactsasanothervariableinthestudy. FACTOR ANALYSIS Withthoselatentvariables,onecanconstructlinearregression analysisandpredictfutureoutcomesorsimplyidentifythe variables'linearrelationship. For example, Goni et al. (2020) considered a Confirmatory factor analysistostudyrespiratorytractinfectionsinHajjandUmrah. They collected the data in the form survey involving 72 variables. In practice,analysingtheentire72variableswillyieldpoorresults. Contd...

7. Thus, the dimensionality reduction technique is adopted and measured confirmatoryfactoranalysis, whichusesthe chi-squarestatistic. Also, Saefi et al. (2020) studied the undergraduate student's knowledge by the about COVID19, measures taken by them to prevent the disease, and maintaining the health styleduringCOVID19. They conducted a survey and investigated the properties of the KAP questionnaire by adopting Confirmatory Factor Analysis (CFA) and RASCH model and the results of these analyses revealed that each of the items in the questionnaire possesses unique qualitiesandthisquestionnaireisadequateenoughtomeasurethestudent's knowledge,attitude and practiceduring COVID19. Contd...

8. Further, Siemieniuk et al. (2020) compared the effects of COVID19 treatments from literatureusingMeta-analysis. DataforthisstudyhasbeencollecteddailyfromdifferentsourcessuchastheWHO website,CentreforDisease ControlandPreventionin theU.S.,PubMed, etc. The data includes detailed information of the patient affected with COVID19, like the lengthof stay in ICU, duration ofventilation, etc.

9. With this information, they conducted a Bayesian meta-analysis and performed 10000 Markov Chain iterations using fixed effects andrandomeffectsseparatelyandfoundnostatistical incoherencein the analysis. BAYESIAN META- ANALYSIS Furthermore, Xu et al. (2020) studied the characteristics of patientsaffectedbyCOVID19outsideWuhanin China. The study revealed that people affected with COVID outside WuhancityareverymildthanthepeopleaffectedinWuhan. Apartfromtheviralinfectiousdisease,numerousdiseasesareof interesttotheresearchersinfindingthecauses,remedies,risk factors,etc. Contd...

10. Onesuchincreasingresearchareaiscancerstudies. Calster et al. (2020) considered a cohort study on ovarian cancer and identified the bestmodel todetect cancerand properlydistinguish cancertypes. The dataset has been collected from IOTA and selected a proper sample for the analysis. Fivedifferentmodelshavebeenconducted,andtheresultsrevealedthatSRRiskand ADNEXmodelsperformedwellinclassifyingthetypeofcancer. Healthcareresearchistodiagnosethediseaseorfindtheriskfactorassociatedwith thedisease. Statisticaltechniquescanbeusedtoanalysethecausesofthediseases. Contd...

11. Inthat sense,Tian etal. (2019) estimatedthe riskfactors ofhospital admission related tocardiovasculardisease. Atotalof184citiesinChinaareincludedinthestudy,andtheinformationrelatedto pollutionand hospital admissionsare collected. TheyadoptedTimeseriesanalysistoinvestigatetheassociationbetweenpollution anddisease. Theresultsshowedthatshort-termexposuretopollutionleadstoincreasedhospital admissionsfor cardiovascular disease. Statsworkprovideshighqualitybiostatisticsserviceswhichhelpspreciseestimationof theeffectsizeandincreasesthegeneralizabilityoftheresultsofindividualstudies.

12. MODELS TO FORECAST THERISK OF COVID-19 IN THE GENERAL POPULATION Theyacknowledgedsevenmodelsthathelpinpredictingthe riskof covid-19in thegeneral population. Three models from one study used hospital admission based on non-tuberculosis pneumonia, influenza, acute bronchitis, or upper respiratory tract infections as substitution outcomes in a datasetwithoutany patientswith covid-191. The fourth model uses a deep learning technique detecting thermal video from the faces of people wearing facemasks to detectingabnormalbreathing(notcovidrelated)witha reportedsensitivityof80%. Contd...

13. Thefifthmodelusesamobileapplicationtocollectdataandtorisk-stratifypatients.Thefifthmodelusesamobileapplicationtocollectdataandtorisk-stratifypatients. Itusesdemographics,symptoms,andcontacthistoryofusers. It further expanded into two more models: blood values and blood values plus computedtomography (C.T.) images.

14. Table:Overviewofpredictionmodelsfordiagnosisandprognosisofcovid-1911Table:Overviewofpredictionmodelsfordiagnosisandprognosisofcovid-1911

15. DIAGNOSTIC MODELS TO DISCOVER COVID-19 IN PATIENTS WITH SUSPECTED INFECTION It is a type of method or test used to help diagnose a diseaseor condition. Itincludesimagingtestsandteststomeasureblood pressure,pulse,andtemperatureareexamplesof diagnostictechniques. Diagnosis has significant implications for patient care, research,and policy.

16. Apredictivemodelwasdefinedascombiningatleasttwo prognostic factors, based on multivariable analysis, as estimating the individual risk of a specific outcome, presented as regression formula,nomogram, orinasimplified form,suchasriskscore. PREDICTIVE MODELSTO DIAGNOSE COVID-19 A predictive model is a formal grouping of multiple predictors from which a particular endpoint's risks can be calculated for individual patients. Othernamesforapredictivemodelincludeprognostic(or prediction) index or rule, risk (or clinical) prediction model, and predictivemodel.

17. Further,statisticaltechniqueshavebeenwidelyusedin epidemiologicalresearch. Moustgaard et al. (2020) studied the impact of treatment and therapeuticallyeffectsinclinicaltrialsusingmeta-analysis. The results showed no difference in the effects of treatments of patientsfromthehealthcareproviderswithandwithoutblinding. Furthermore, Fabbri et al. (2020) presented a review on the health care providers and South African patients' funding using meta-analysis. CONCLUSION

18. Theyrecommendedthatthecorporatecompaniesprovidetransparencyin providing funds to patients, and this type of funding can be seen in high-income countries. Ifyouarestrugglingwithmeta-analysisyoucanreachourstatisticalmeta-analysis service.

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