Version 1.0 — Published July 2026
Quick Answer
PSM (Preventive and Social Medicine, also called Community Medicine) contributes 20-30 questions per NEET PG paper — one of the largest single-subject shares. The 14 most expensive mistakes cluster around epidemiology fundamentals, biostatistics, national health programmes, and vital statistics. To protect these marks:
- Distinguish incidence from prevalence — incidence measures new cases and risk; prevalence measures existing cases and burden; P equals I times D in steady state
- Match measure to study design — RCT and cohort use RR; case-control uses OR; survival analysis uses HR
- Rank study design strength — RCT above cohort above case-control above cross-sectional above ecological; know each design's strengths and limitations
- Nail the 2x2 diagnostic table — sensitivity is TP over (TP plus FN); specificity is TN over (TN plus FP); PPV and NPV depend on prevalence; sensitivity and specificity do not
- Learn the Wilson-Jungner screening criteria — condition-test-programme
- Distinguish confounder, effect modifier, and mediator — different roles in causal inference and different analytic handling
- Recognise the bias family — selection (Berkson, healthy worker, non-response), information (recall, interviewer, misclassification), lead-time and length-time in screening
- Choose the right sampling method — probability (simple random, systematic, stratified, cluster, multistage) for population inference; non-probability (convenience, quota, purposive, snowball) for pragmatic or hidden-population studies
- Lock the RCH schemes — JSY (cash incentive for institutional delivery), JSSK (free everything for delivery and neonatal care), PMSMA (free ANC on 9th every month), LaQshya (labour room quality), SUMAN (assured free MCH)
- Learn the UIP schedule cold — BCG plus OPV-0 plus HepB-0 at birth, Penta plus OPV plus fIPV plus rotavirus plus PCV at 6-10-14 weeks, MR plus JE plus PCV-booster plus vitamin A at 9 months, DPT booster plus OPV booster plus MR-2 at 16-24 months
- Memorise India's current vital statistics — IMR, U5MR, MMR, TFR, CBR, CDR, life expectancy
- Know the demographic transition stages I-IV — India is currently in late stage III moving to stage IV
- Recite the National Health Policy 2017 goals and SDG 3 targets — health expenditure 2.5 percent of GDP by 2025; SDG 3.1 MMR under 70; SDG 3.2 U5MR under 25 and NMR under 12
- Distinguish similar terms — epidemic vs endemic vs pandemic; primary vs secondary vs tertiary prevention; notifiable diseases
Why PSM mistakes are especially costly
PSM is the single largest subject in NEET PG by question count and one of the highest-scoring subjects for candidates who prepare it systematically. The subject rewards structured memorisation — programmes, definitions, formulas, schedules — but punishes students who conflate similar-sounding concepts (incidence vs prevalence, OR vs RR, PPV vs NPV) or who miss updates to national programmes.
Each PSM MCQ is worth the same as an MCQ in medicine or surgery, but the marginal preparation time to lift PSM accuracy is much lower because the content set is finite and well-defined. This makes PSM one of the highest ROI subjects in your preparation — and the 14 mistakes below the fastest way to lift your score by 5-10 marks.
Mistake 1: Confusing incidence and prevalence
Why students get it wrong: The two words sound similar, and both are population health measures.
How to remember it correctly:
| Measure | Definition | When to use | Formula |
|---|
| Incidence rate | New cases per person-time at risk | Risk of developing disease; outbreak investigation; primary prevention evaluation | New cases divided by person-time at risk |
| Cumulative incidence (attack rate) | New cases per persons at risk over fixed period | Outbreak, closed cohort | New cases divided by persons at risk |
| Point prevalence | Proportion with disease at a point in time | Disease burden; health-service planning | Existing cases divided by population at that point |
| Period prevalence | Proportion with disease during a period | Chronic disease with variable duration | Existing plus new cases divided by average population |
Key equation: P equals I times D in steady state — prevalence is the product of incidence and average duration.
Trap: using prevalence to compare exposure groups. Prevalence conflates risk and duration; incidence isolates risk. Always use incidence for causal comparisons.
Trap 2: confusing incidence rate (per person-time) with cumulative incidence (per persons at risk). Incidence rate can exceed 1; cumulative incidence cannot.
Mistake 2: Confusing odds ratio, relative risk, and hazard ratio
Why students get it wrong: All three are ratio measures of association and all sound similar.
How to remember it correctly:
| Measure | Study design | Definition | Interpretation |
|---|
| Relative Risk (RR) | Cohort, RCT | Incidence in exposed divided by incidence in unexposed | 2.0 means twice the risk in the exposed |
| Odds Ratio (OR) | Case-control | Odds of exposure in cases divided by odds of exposure in controls | Approximates RR when disease is rare (under 10 percent) |
| Hazard Ratio (HR) | Cox regression (survival analysis) | Ratio of instantaneous hazards over follow-up | 2.0 means twice the instantaneous risk at any time point |
Trap: using OR for a cohort study. Cohort studies allow direct incidence measurement, so RR is preferred; OR is only necessary when incidence cannot be measured (case-control). Using OR in a cohort study overestimates RR when the outcome is common.
Trap 2: interpreting HR as a cumulative measure. HR is instantaneous; a HR of 2.0 does not mean twice the overall event count — it means twice the risk at each moment during follow-up.
Mistake 3: Ranking study designs incorrectly
Why students get it wrong: The evidence hierarchy is not always intuitive, and each design has situations where it is the only option.
How to remember it correctly: From strongest to weakest evidence for causal inference:
- Systematic review and meta-analysis of RCTs — highest evidence
- Randomised controlled trial (RCT) — randomisation eliminates confounding; the gold standard for efficacy
- Cohort study — measures incidence and relative risk; limited by confounding
- Case-control study — efficient for rare diseases; limited by recall bias and selection bias
- Cross-sectional study — measures prevalence; cannot establish temporality
- Ecological study — population-level; risks ecological fallacy
- Case series and case report — hypothesis-generating only
Strengths and weaknesses to memorise:
| Design | Strengths | Weaknesses |
|---|
| RCT | Causal inference, randomisation eliminates confounding, best for efficacy | Expensive, ethical constraints, narrow eligibility limits generalisability |
| Cohort (prospective) | Direct incidence, temporality clear, multiple outcomes | Long follow-up, loss to follow-up, expensive |
| Cohort (retrospective) | Faster, cheaper | Data quality issues |
| Case-control | Rare disease efficient, cheap, quick, multiple exposures | Recall bias, selection of controls, no incidence |
| Cross-sectional | Fast, cheap, prevalence estimates | No temporality, cannot infer causation |
| Ecological | Population-level trends | Ecological fallacy |
Trap: case-control is retrospective by design; cohort can be prospective or retrospective. Do not conflate temporality with directionality.
Mistake 4: Botching the 2x2 diagnostic test table
Why students get it wrong: Six numbers, four measures, formulae look similar.
How to remember it correctly:
| Disease + | Disease - |
|---|
| Test + | TP | FP |
| Test - | FN | TN |
- Sensitivity equals TP divided by (TP plus FN) — the proportion of diseased correctly detected
- Specificity equals TN divided by (TN plus FP) — the proportion of non-diseased correctly excluded
- PPV equals TP divided by (TP plus FP) — of test positives, how many have disease
- NPV equals TN divided by (TN plus FN) — of test negatives, how many are truly disease-free
- LR+ equals sensitivity divided by (1 minus specificity)
- LR- equals (1 minus sensitivity) divided by specificity
Mnemonics:
- SnOUT — a highly Sensitive test with a Negative result rules OUT disease (few false negatives)
- SpIN — a highly Specific test with a Positive result rules IN disease (few false positives)
Key principle: sensitivity and specificity are intrinsic to the test and do not vary with prevalence. PPV rises and NPV falls as prevalence rises. In a low-prevalence population (screening asymptomatic people), even a highly specific test produces mostly false positives, making PPV low.
Trap: treating PPV as a fixed test property. Always consider the pre-test probability (prevalence).
Mistake 5: Ignoring Wilson-Jungner screening criteria
Why students get it wrong: The list has 10 items; students memorise 3-4.
How to remember it correctly: Wilson-Jungner (1968) criteria for a screening programme, grouped:
Condition:
- Important health problem
- Recognisable latent or early symptomatic stage
- Natural history well-understood
Test:
4. Suitable test — sensitive, specific, safe, acceptable, cheap
5. Test acceptable to population
Treatment:
6. Accepted effective treatment
7. Facilities for diagnosis and treatment available
8. Agreed policy on whom to treat
Programme:
9. Case-finding continuous, not one-off
10. Cost balanced with benefit
Trap: confusing screening (asymptomatic population) with diagnostic testing (symptomatic patient). Screening tests need high sensitivity to catch all cases and reasonable specificity; diagnostic tests need high specificity.
Mistake 6: Confusing confounder, effect modifier, and mediator
Why students get it wrong: All three terms describe a third variable's relationship to exposure and outcome.
How to remember it correctly:
- Confounder — a variable associated with both exposure and outcome, distorting the observed exposure-outcome relationship. Example: age confounds the coffee-heart-disease association. Handle by matching, stratification (Mantel-Haenszel), or multivariable regression.
- Effect modifier (interaction) — a variable that modifies the strength of the exposure-outcome relationship in different strata. Example: sex modifies the alcohol-hepatotoxicity association. Handle by reporting stratum-specific estimates; do NOT adjust away.
- Mediator — a variable on the causal pathway from exposure to outcome. Example: HDL mediates the exercise-CV-mortality association. Handle by mediation analysis (do NOT adjust away if you want the total effect).
Trap: adjusting for a mediator when you want the total effect — this attenuates the estimate. Adjusting for a confounder is required for causal inference.
Mistake 7: Missing bias types in study interpretation
Why students get it wrong: Bias is a large family and the terms overlap.
How to remember it correctly: Bias groups:
Trap: confusing lead-time and length-time bias. Lead-time = same disease detected earlier; length-time = detection favours slow-growing disease.
Mistake 8: Choosing the wrong sampling method
Why students get it wrong: Terminology is inconsistent across textbooks.
How to remember it correctly:
Probability sampling (every individual has a known non-zero probability of selection — required for population inference):
- Simple random — every individual has equal probability; sample with random-number table or software
- Systematic — every kth individual after a random start
- Stratified — divide population into strata (age, sex, region), sample within each; ensures representation of all strata
- Cluster — divide into naturally occurring clusters (villages, schools), sample entire clusters; used when a sampling frame is not available
- Multistage — combines the above; NFHS uses this
Non-probability sampling (individuals do not have known selection probability — used for pragmatic, hidden population, or hypothesis-generating studies):
- Convenience — take who is available
- Quota — fill fixed quotas without random selection within quota
- Purposive — select information-rich individuals
- Snowball — one participant recruits the next; used for hidden populations (IDU, MSM)
Trap: thinking cluster sampling is non-probability. It is probability sampling but with lower statistical efficiency (design effect greater than 1).
Mistake 9: Confusing RCH schemes (JSY vs JSSK vs PMSMA)
Why students get it wrong: Multiple schemes with overlapping objectives.
How to remember it correctly:
| Scheme | Launch | Content |
|---|
| JSY (Janani Suraksha Yojana) | 2005 | Cash incentive Rs 700-1400 for institutional delivery in BPL women |
| JSSK (Janani Shishu Suraksha Karyakram) | 2011 | Free delivery, free caesarean, free drugs, free diagnostics, free diet, free transport, free treatment of sick newborn up to 30 days (extended to 1 year in 2013) |
| PMSMA (Pradhan Mantri Surakshit Matritva Abhiyan) | 2016 | Free ANC on the 9th of every month by obstetrician or trained MO for 2nd and 3rd trimester pregnant women |
| LaQshya (Labour Room Quality Improvement) | 2017 | Labour room and maternity OT quality certification |
| SUMAN (Surakshit Matritva Aashwasan) | 2019 | Assured free maternal and neonatal service; extension of JSSK to 6 months (later 1 year) |
| MAA (Mothers Absolute Affection) | 2016 | Breastfeeding promotion |
| RBSK (Rashtriya Bal Swasthya Karyakram) | 2013 | Child health screening for 4 Ds (defects, deficiencies, diseases, developmental delays) up to 18 years |
| RKSK (Rashtriya Kishor Swasthya Karyakram) | 2014 | Adolescent health 10-19 years |
Trap: confusing JSY (cash to mother) with JSSK (free services for mother and neonate). Both cover delivery but different mechanisms.
Mistake 10: Missing UIP schedule details
Why students get it wrong: Multiple time points and multiple vaccines per point.
How to remember it correctly:
| Age | Vaccines |
|---|
| Birth | BCG, OPV-zero, Hepatitis B-zero |
| 6 weeks | Penta (DPT plus Hep-B plus Hib), OPV-1, fIPV-1, Rotavirus-1, PCV-1 |
| 10 weeks | Penta-2, OPV-2, Rotavirus-2 |
| 14 weeks | Penta-3, OPV-3, fIPV-2, Rotavirus-3, PCV-2 |
| 9-12 months | MR-1 (measles-rubella), JE-1 (endemic districts), PCV booster, Vitamin A-1 |
| 16-24 months | DPT booster-1, OPV booster, MR-2, JE-2, Vitamin A-2 |
| 5-6 years | DPT booster-2 |
| 10 years | Td (tetanus-diphtheria) |
| 16 years | Td |
| Pregnancy | Td 4-8 weeks apart, 2 doses in a first pregnancy or booster if last dose more than 5 years |
| Vitamin A | 9 doses at 9 months, then every 6 months up to 5 years |
Trap: confusing PCV schedule (6, 14 weeks, plus 9-month booster) with rotavirus (6, 10, 14 weeks — all 3 primary doses). PCV in India follows a 2p+1b schedule after 2017 revision.
Mistake 11: Misremembering India's current vital statistics
Why students get it wrong: Numbers change annually with SRS and NFHS updates.
How to remember it correctly: Approximate current values (SRS 2020, NFHS-5 2019-21 — verify latest before exam):
| Indicator | Definition | India current | SDG 3 / NHP 2017 target |
|---|
| CBR (crude birth rate) | Live births per 1000 population per year | ~19 | — |
| CDR (crude death rate) | Deaths per 1000 population per year | ~7 | — |
| NMR (neonatal mortality rate) | Deaths under 28 days per 1000 live births | ~20 | Under 12 (SDG) |
| IMR (infant mortality rate) | Deaths under 1 year per 1000 live births | ~28 | Under 12 (NHP 2017 target 28 was 2019) |
| U5MR (under-5 mortality rate) | Deaths under 5 years per 1000 live births | ~32 | Under 25 (SDG 3.2) |
| MMR (maternal mortality ratio) | Maternal deaths per 100,000 live births | ~97 (SRS 2018-20) | Under 70 (SDG 3.1); NHP 100 by 2020 (achieved) |
| TFR (total fertility rate) | Avg children per woman | 2.0 (NFHS-5) | Below replacement 2.1 (achieved) |
| Life expectancy at birth | Years | ~70 (male 68, female 71) | 70 by 2025 (NHP) |
Trap: using NMR when the question asks IMR. NMR is under 28 days; IMR is under 1 year (includes NMR plus post-neonatal deaths up to 12 months).
Mistake 12: Misordering the demographic transition stages
Why students get it wrong: Four stages with paired CBR and CDR patterns.
How to remember it correctly:
| Stage | CBR | CDR | Population growth |
|---|
| I — pre-transition | High | High | Static or slow |
| II — early transition | High | Falling | Rapid growth (population explosion) |
| III — late transition | Falling | Low | Slowing growth |
| IV — post-transition | Low | Low | Static or declining |
India is currently in late stage III — CBR ~19 (falling), CDR ~7 (low), TFR 2.0 (just below replacement). Kerala and Tamil Nadu are in stage IV; northern states like Bihar and UP are still in stage III.
Mistake 13: Muddling National Health Policy 2017 goals and SDG 3 targets
Why students get it wrong: Two overlapping frameworks with different numeric targets.
How to remember it correctly:
NHP 2017 selected goals:
- Increase health expenditure to 2.5 percent of GDP by 2025 (currently ~1.3-1.8 percent)
- Increase life expectancy at birth from 67.5 to 70 by 2025
- Reduce IMR to 28 by 2019 (achieved)
- Reduce U5MR to 23 by 2025
- Reduce MMR to 100 by 2020 (achieved — 97 in 2018-20)
- Reduce TFR to 2.1 by 2025 (achieved — 2.0 in NFHS-5)
- 90-90-90 HIV target by 2020
- Elimination of leprosy by 2018 (largely achieved), kala-azar by 2017, filariasis by 2017
- 80 percent NCD screening by 2025
SDG 3 selected targets by 2030:
- 3.1 — MMR under 70 per 100,000 live births globally
- 3.2 — NMR under 12 per 1000 live births and U5MR under 25 per 1000 live births
- 3.3 — end HIV, TB, malaria, hepatitis, NTD epidemics
- 3.4 — reduce premature NCD mortality by one-third
- 3.5 — substance abuse prevention and treatment
- 3.6 — halve road traffic deaths
- 3.7 — universal access to reproductive health services
- 3.8 — universal health coverage
- 3.9 — reduce environmental deaths
Trap: confusing SDG 3.1 (MMR) with SDG 3.2 (NMR and U5MR). SDG 3.1 is single-metric; SDG 3.2 has two paired metrics.
Mistake 14: Confusing similar terms — epidemic, pandemic, endemic; primary vs secondary vs tertiary prevention
Why students get it wrong: Words used loosely in ordinary speech.
How to remember it correctly:
Epidemic vs pandemic vs endemic:
- Endemic — usual expected level of disease in a population
- Epidemic (outbreak) — occurrence in excess of the usual level
- Pandemic — epidemic across multiple continents affecting a large proportion of the population
- Hyperendemic — persistently high level of endemic disease
- Sporadic — irregular unpredictable cases
Primary vs secondary vs tertiary prevention:
- Primordial — preventing risk factors from developing (e.g. tobacco tax, sugar tax)
- Primary — preventing disease onset in healthy people (e.g. vaccination, health promotion)
- Secondary — early detection of asymptomatic disease and prompt treatment (e.g. screening — mammography, Pap smear, HbA1c screening)
- Tertiary — reducing morbidity, disability, and complications in established disease (e.g. cardiac rehabilitation, diabetic foot care)
- Quaternary — protecting patients from unnecessary medical interventions
Notifiable vs non-notifiable diseases:
- Internationally notifiable (WHO) — cholera, plague, yellow fever, SARS, Ebola, novel influenza, polio, MERS
- Nationally notifiable (India) — TB, HIV, malaria, dengue, chikungunya, kala-azar, leprosy, viral hepatitis, meningococcal disease, measles, mumps, rubella, tetanus, diphtheria, whooping cough, food poisoning, plague, cholera, Japanese encephalitis, acute encephalitis syndrome, and many more; list state-varying — check state health department
Trap: confusing screening with primary prevention. Screening is secondary prevention.
How NEET PG tests PSM
Six recurring patterns.
Pattern 1 — Incidence vs prevalence question: A vignette gives a disease with high prevalence and asks about risk. Answer with incidence. If the vignette asks about disease burden, answer with prevalence.
Pattern 2 — Study-design measure question: A vignette describes a case-control study and asks the appropriate measure. Answer: odds ratio. For a cohort or RCT: relative risk. For survival analysis: hazard ratio.
Pattern 3 — Sensitivity/specificity/PPV question: A vignette gives a 2x2 table and asks a specific measure. Learn the formulas cold: sensitivity = TP over (TP plus FN); specificity = TN over (TN plus FP); PPV = TP over (TP plus FP); NPV = TN over (TN plus FN).
Pattern 4 — RCH scheme identification question: A vignette describes cash incentive for institutional delivery = JSY. Free delivery plus caesarean plus drugs plus transport plus neonatal care = JSSK. Free ANC on the 9th of every month = PMSMA. Labour room quality = LaQshya. Assured free MCH = SUMAN.
Pattern 5 — UIP vaccine timing question: Which vaccine at 6 weeks? Penta (DPT plus Hep-B plus Hib), OPV-1, fIPV-1, rotavirus-1, PCV-1. At 9 months? MR-1 (measles-rubella), JE-1 (endemic), PCV booster, Vitamin A-1. At birth? BCG, OPV-zero, Hep-B-zero.
Pattern 6 — Bias question: Cases remember exposures better than controls = recall bias. Hospitalised controls differ from community = Berkson bias. Screening finds slow-growing disease preferentially = length-time bias. Screening detects earlier without benefit = lead-time bias.
High-yield one-liners:
- Incidence measures risk; prevalence measures burden; P = I times D in steady state
- RCT and cohort use RR; case-control uses OR; survival analysis uses HR
- Sensitivity rules OUT (SnOUT); specificity rules IN (SpIN)
- Sensitivity and specificity do not vary with prevalence; PPV and NPV do
- Wilson-Jungner criteria — condition, test, treatment, programme; know all 10
- Confounder distorts; effect modifier modifies by stratum; mediator lies on the causal path
- Recall bias is the biggest weakness of case-control studies
- Berkson bias is a hospital-based selection bias
- Cluster sampling is probability sampling with a design effect greater than 1
- JSY = cash for institutional delivery; JSSK = free services; PMSMA = free ANC on the 9th
- UIP at 6-10-14 weeks — Penta, OPV, Rotavirus (all 3), PCV (6 and 14 only), fIPV (6 and 14 only)
- MR at 9 months, MR-2 at 16-24 months
- India IMR ~28, MMR ~97, TFR 2.0, life expectancy ~70 (verify latest SRS/NFHS)
- India is in late demographic transition stage III
- NHP 2017 — 2.5 percent GDP on health by 2025
- SDG 3.1 = MMR under 70; SDG 3.2 = NMR under 12 and U5MR under 25 by 2030
- Screening is secondary prevention
Frequently Asked Questions
How many PSM and community medicine questions appear in NEET PG and what are the highest-yield clusters?
PSM (Preventive and Social Medicine, also called Community Medicine) contributes approximately 20-30 questions per NEET PG paper, one of the largest single-subject shares of the exam. The highest-yield clusters are (1) epidemiology fundamentals — incidence vs prevalence, the relationship P equals I times D, standardisation of rates, and epidemic-endemic-pandemic terminology; (2) study designs — RCT, cohort, case-control, cross-sectional, ecological, with their strengths and weaknesses, and the measures each generates (RR, OR, HR); (3) diagnostic test performance — sensitivity, specificity, PPV, NPV, LR+, LR-, prevalence-dependence of PPV and NPV, and the Wilson-Jungner screening criteria; (4) bias and confounding — selection bias, information bias, recall bias, Berkson bias, healthy worker effect, lead-time bias, length-time bias, confounder vs effect modifier vs mediator; (5) sampling methods — probability sampling (simple random, systematic, stratified, cluster, multistage) and non-probability sampling (convenience, quota, purposive, snowball); (6) India-specific national health programmes — RCH (JSY, JSSK, LaQshya, PMSMA, SUMAN), NPCDCS, RNTCP now NTEP, NLEP, NVBDCP, IDSP, and the UIP immunisation schedule; (7) vital statistics — CBR, CDR, IMR, U5MR, MMR, TFR, life expectancy, with India's current values; (8) demographic transition stages I-IV and India's current position; (9) National Health Policy 2017 goals and SDG 3 targets; and (10) confusing similar terms — pandemic vs epidemic vs endemic, primary vs secondary vs tertiary prevention, notifiable vs non-notifiable diseases. The 14 mistakes in this guide cover roughly 75-85 percent of typical PSM question failures.
What is the difference between incidence and prevalence and why does the equation P equals I times D matter?
Incidence and prevalence are the two foundational epidemiologic measures, and confusing them is one of the most common PSM errors on NEET PG. Incidence is the rate of new cases occurring in a defined population over a defined time period, expressed either as incidence rate (new cases per person-time at risk — e.g. 5 new cases per 1000 person-years) or as cumulative incidence or attack rate (new cases per persons at risk over a fixed period — e.g. 5 per 1000 over a year). Incidence measures the risk of developing disease and is the correct measure for causal inference, outbreak investigation, and evaluating primary prevention. Prevalence is the proportion of a defined population that has a condition at a defined time point (point prevalence) or over a defined period (period prevalence). Prevalence measures the burden of disease and is the correct measure for resource planning, healthcare delivery, and evaluating chronic disease control. The relationship P equals I times D (in steady state) means that prevalence depends on both incidence and duration — a disease with low incidence but long duration (like chronic HIV on ART) can have high prevalence, and a disease with high incidence but short duration (like seasonal influenza) can have low point prevalence. NEET PG tests the equation, the steady-state assumption, and the differential appropriateness of the two measures — e.g. do NOT use prevalence to compare risk between exposure groups (use incidence).
What is the difference between odds ratio, relative risk, and hazard ratio and when is each used?
The three measures of association differ by study design and the type of outcome. Relative risk (RR) is the ratio of incidence in the exposed group to incidence in the unexposed group; it is calculated in cohort studies and randomised controlled trials where the researcher measures who develops the outcome over follow-up. RR of 2.0 means exposed individuals have twice the risk. Odds ratio (OR) is the ratio of the odds of exposure in cases to the odds of exposure in controls; it is calculated in case-control studies where the researcher starts with the outcome (cases and controls) and looks back at exposure. OR is used because incidence cannot be measured in a case-control design. When outcomes are rare (less than 10 percent), OR approximates RR closely; when outcomes are common, OR overestimates RR. Hazard ratio (HR) is a measure of the ratio of instantaneous hazard rates over follow-up in exposed vs unexposed groups, calculated by Cox proportional hazards regression. HR of 2.0 means at any given time point during follow-up, the instantaneous risk of the outcome in the exposed group is twice that of the unexposed. HR is preferred in survival analysis (censored data, time-to-event outcomes such as death, relapse, MI). NEET PG tests the study-design pairing (RCT and cohort use RR, case-control uses OR, survival analysis uses HR) and the rare-disease OR approximates RR rule most commonly.
How are sensitivity, specificity, PPV and NPV calculated from a 2x2 table and how does prevalence affect them?
A 2x2 diagnostic test performance table has True Positives (TP), False Positives (FP), True Negatives (TN), and False Negatives (FN) arranged with the disease status in columns and the test result in rows. Sensitivity is TP divided by (TP plus FN) — the proportion of diseased individuals correctly identified by the test; a highly sensitive test rules OUT disease when negative (SnOUT). Specificity is TN divided by (TN plus FP) — the proportion of non-diseased individuals correctly identified; a highly specific test rules IN disease when positive (SpIN). Sensitivity and specificity are intrinsic properties of the test and do NOT change with population prevalence. Positive predictive value (PPV) is TP divided by (TP plus FP) — the probability that a positive test result reflects true disease. Negative predictive value (NPV) is TN divided by (TN plus FN) — the probability that a negative test result reflects true absence of disease. PPV and NPV are strongly affected by disease prevalence — in a low-prevalence population, PPV falls dramatically even with a highly specific test because false positives outnumber true positives; in a high-prevalence population, PPV rises and NPV falls. This is why screening asymptomatic populations for rare diseases with imperfect tests produces mostly false positives, and why confirming screen-positive results with a more specific second test is essential. The likelihood ratios LR+ (sensitivity divided by 1 minus specificity) and LR- (1 minus sensitivity divided by specificity) are prevalence-independent and are used in Bayesian updating of pre-test to post-test probability. NEET PG tests the 2x2 formulas and prevalence-dependence of PPV and NPV heavily.
What are the key national RCH programmes in India and what does the UIP schedule contain?
The Reproductive and Child Health (RCH) programme is delivered under the National Health Mission (NHM) and includes several flagship India-specific schemes. Janani Suraksha Yojana (JSY) — a cash-incentive scheme for institutional delivery, launched 2005, gives Rs 700-1400 to BPL women. Janani Shishu Suraksha Karyakram (JSSK) — launched 2011, provides free delivery, free caesarean, free drugs and diagnostics, free diet, free transport (home-to-facility and back), and free treatment of sick neonates up to 30 days (extended to 1 year for illness in 2013) to any pregnant woman and sick newborn in a public facility. LaQshya (Labour Room Quality Improvement Initiative) — launched 2017, focuses on quality improvement in labour rooms and maternity operating theatres in public facilities with certification levels. Pradhan Mantri Surakshit Matritva Abhiyan (PMSMA) — launched 2016, provides free antenatal check-up on the 9th of every month by an obstetrician or trained MO for pregnant women in their 2nd and 3rd trimesters. SUMAN (Surakshit Matritva Aashwasan) — launched 2019, provides assured free service for maternal and neonatal care to any pregnant woman and neonate up to 6 months (extension of JSSK). The Universal Immunisation Programme (UIP) is delivered under RCH and includes BCG plus OPV-zero plus hepatitis B-zero at birth, Penta (DPT plus Hep-B plus Hib) plus OPV plus fIPV plus rotavirus plus PCV at 6-10-14 weeks, MR (measles-rubella) plus JE (in endemic districts) plus PCV booster plus vitamin A at 9-12 months, DPT booster plus OPV booster plus MR-2 plus JE-2 plus vitamin A at 16-24 months, DPT booster at 5-6 years, Td at 10 and 16 years, and Td for pregnant women at 4-8 weeks and after 16 weeks apart. NEET PG tests the JSY vs JSSK vs PMSMA distinction and the UIP schedule (birth, 6-10-14, 9, 16-24 months) most commonly.
This content is for educational purposes for NEET PG exam preparation. It is not a substitute for professional medical advice, diagnosis, or treatment. Clinical information has been reviewed by qualified medical professionals.
Written by: NEETPGAI Editorial Team
Reviewed by: Pending SME Review
Last reviewed: July 2026
