Rishi Desai, MD, MPH

Vaccination and herd immunity

VACCINATION & HERD IMMUNITY osms.it/vaccination-herd-immunity HERD IMMUNITY BASICS  ▪ Herd immunity: phenomenon in which entire population is indirectly protected against disease when critical percentage of members are immune ▫ Immunity can be innate/acquired through vaccination/by naturally recovering from infection ▫ The higher the proportion of immune people in a population, the less likely the encounter between a susceptible person and an infected one → chain of infection is disrupted  Conditions ▪ Host is a single species ▪ Transmission of the organism must be spread by direct contact ▪ No reservoir outside the human host ▪ Infections must induce solid immunity  54  OSMOSIS.ORG  HERD IMMUNITY & COMMUNITY HEALTH  ▪ The critical percentage of immune individuals needed to achieve herd immunity varies according to disease contagiousness (e.g. 94% in measles [highly communicable] → increased number of individuals need to be immune) ▪ Because of herd immunity, vaccination programs do not necessitate yield 100% immunization rates, yet can achieve highly effective protection by immunizing critical percentage of a population ▪ Herd immunity is important for public health because individuals who cannot develop immunity or cannot be vaccinated depend on herd immunity (e.g. newborn infants, individuals with immunodeﬁciency due to HIV/AIDS, cancer, cancer treatments)   

Introduction to biostatistics

Probability

Types of data

Chi-squared test

Fisher's exact test

Kaplan-Meier survival analysis

Kappa coefficient

Mann-Whitney U test

Spearman's rank correlation coefficient

Non-parametric tests

Type I and type II errors

Outcomes of statistical hypothesis testing

Correlation

Hypothesis testing: One-tailed and two-tailed tests

Linear regression

Logistic regression

Methods of regression analysis

One-way ANOVA

Paired t-test

Repeated measures ANOVA

Two-sample t-test

Two-way ANOVA

Parametric tests

Mean, median, and mode

Normal distribution and z-scores

Range, variance, and standard deviation

Standard error of the mean (Central limit theorem)

Statistical probability distributions

Biostatistics

Bias in interpreting results of clinical studies

Bias in performing clinical studies

Confounding

Disease causality

Information bias

Interaction

Selection bias

Causation, validity, and bias

Attributable risk (AR)

DALY and QALY

Direct standardization

Incidence and prevalence

Indirect standardization

Mortality rates and case-fatality

Odds ratio

Relative and absolute risk

Epidemiological measurements

Positive and negative predictive value

Sensitivity and specificity

Test precision and accuracy

Evaluation of diagnostic tests

Disease surveillance

Modes of infectious disease transmission

Outbreak investigations

Prevention

Public health

Case-control study

Clinical trials

Cohort study

Cross sectional study

Ecologic study

Placebo effect and masking

Randomized control trial

Sample size

Study designs

Study design

Epidemiology

Vaccination and herd immunity

Videos

Notes