Class EpidemiologyStats

java.lang.Object

org.episteme.natural.medicine.epidemiology.EpidemiologyStats

public class EpidemiologyStats
extends Object

Epidemiological statistics calculations.

Since:

1.0

Author:

Silvere Martin-Michiellot, Gemini AI (Google DeepMind)

Method Summary

Modifier and Type	Method	Description
static Real	incidenceRate(int newCases, int populationAtRisk)	Incidence rate = new cases / population at risk
static Real	negativePredictiveValue(int trueNegative, int falseNegative)	Negative Predictive Value = TN / (TN + FN)
static Real	numberNeededToTreat(Real controlEventRate, Real treatmentEventRate)	Number Needed to Treat = 1 / ARR
static Real	oddsRatio(int a, int b, int c, int d)	Odds ratio from 2x2 contingency table.
static Real	positivePredictiveValue(int truePositive, int falsePositive)	Positive Predictive Value = TP / (TP + FP)
static Real	prevalence(int totalCases, int totalPopulation)	Prevalence = total cases / total population
static Real	relativeRisk(int a, int b, int c, int d)	Relative risk.
static Real	sensitivity(int truePositive, int falseNegative)	Sensitivity = TP / (TP + FN)
static Real	specificity(int trueNegative, int falsePositive)	Specificity = TN / (TN + FP)

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

incidenceRate

public static Real incidenceRate(int newCases,
 int populationAtRisk)

Incidence rate = new cases / population at risk

prevalence

public static Real prevalence(int totalCases,
 int totalPopulation)

Prevalence = total cases / total population

oddsRatio

public static Real oddsRatio(int a,
 int b,
 int c,
 int d)

Odds ratio from 2x2 contingency table. OR = (a*d) / (b*c)

relativeRisk

public static Real relativeRisk(int a,
 int b,
 int c,
 int d)

Relative risk. RR = (a/(a+b)) / (c/(c+d))

sensitivity

public static Real sensitivity(int truePositive,
 int falseNegative)

Sensitivity = TP / (TP + FN)

specificity

public static Real specificity(int trueNegative,
 int falsePositive)

Specificity = TN / (TN + FP)

positivePredictiveValue

public static Real positivePredictiveValue(int truePositive,
 int falsePositive)

Positive Predictive Value = TP / (TP + FP)

negativePredictiveValue

public static Real negativePredictiveValue(int trueNegative,
 int falseNegative)

Negative Predictive Value = TN / (TN + FN)

numberNeededToTreat

public static Real numberNeededToTreat(Real controlEventRate,
 Real treatmentEventRate)

Number Needed to Treat = 1 / ARR