prevalence and risk factors of influenza (flu)

Disease and Geography: Influenza (Flu)

1. Why Influenza Is a Geographical Topic (Key Concepts)

Influenza illustrates every one of the eight key concepts required for Paper 4 (Geography 9696). The table below shows how the case study maps onto each concept and how the same analytical steps could be applied to another disease (e.g. malaria) or a non‑health theme (e.g. tourism).

2. Global Spatial Distribution (2023 data)

World Health Organization (WHO, 2023) estimates that each year influenza causes 3–5 million severe cases and 290 000–650 000 respiratory deaths.

3. Drivers of Spatial Patterns

• Climate & seasonality: Winter peaks in temperate zones; rainy‑season peaks in some tropical regions where humidity briefly falls.
• Population density & urbanisation: Crowded housing, schools and public transport increase contact rates.
• Mobility & connectivity: International air travel spreads novel strains within days (e.g., 2009 H1N1).
• Health‑system capacity: Availability of vaccines, antivirals and intensive‑care beds reduces mortality.
• Socio‑economic status: Low‑income groups often have lower vaccine uptake and higher exposure in informal settlements.
• Age structure: Countries with larger elderly populations (e.g., Japan) experience higher severe‑case rates.

4. Change Over Time – Historic Pandemics

Key observations (data sourced from WHO & CDC, 2022):

• 1918 (H1N1) – ≈50 million deaths; limited surveillance, no vaccines.
• 1957 (H2N2) & 1968 (H3N2) – mortality reduced thanks to improved medical care and early vaccine use.
• 2009 (H1N1) – rapid global spread via air travel; mortality lower than 1918 but highlighted the importance of real‑time surveillance.
• 2020‑2022 – COVID‑19 control measures suppressed the 2020‑21 flu season; a rebound in 2022 illustrates interaction between simultaneous pandemics.

5. Place‑Based Inequality – Detailed Country Comparisons

Evaluation snapshot (≈150 words) – see Section 10.2 for the full AO3 task.

6. Risk Factors for Infection (Geographically Linked)

• Age: Children < 5 yr (high contact in schools) and elderly > 65 yr (weaker immunity).
• Underlying health conditions: asthma, cardiovascular disease, diabetes, HIV/AIDS – prevalence varies regionally.
• Living conditions: Overcrowded housing, refugee camps, prisons – concentrated in low‑income urban districts.
• Occupational exposure: Health‑care workers, teachers, public‑transport staff – urban‑centric.
• Seasonal climate: Winter in temperate zones; rainy‑season peaks in some tropical high‑humidity areas.
• Vaccination status: Lower coverage in remote or economically disadvantaged communities.

7. Systems Perspective – Virus‑Host‑Environment‑Health Service Model

8. Impacts of Influenza Outbreaks

1. Health impact: Increased morbidity, ICU pressure, excess mortality (especially among the elderly and those with comorbidities).
2. Economic impact: Loss of productivity (average 1–2 weeks sick leave per case), cost of hospital care, and vaccine procurement.
3. Social impact: School closures, disruption of public services, heightened anxiety during pandemic threats.

9. Management & Control Strategies (Geographical Application)

• Surveillance: WHO Global Influenza Surveillance and Response System (GISRS) and national sentinel networks provide weekly ILI data; GIS mapping of hotspots guides targeted interventions.
• Vaccination programmes:
  • Annual reformulation based on circulating sub‑types (WHO, 2023 vaccine composition).
  • Prioritise high‑risk groups (elderly, health‑workers, pregnant women).
  • Case‑study comparison:
    • United Kingdom: Universal free vaccination for all ≥65 yr and clinical risk groups; high coverage (58 %).
    • South Africa: Targeted high‑risk approach (elderly, HIV‑positive, health‑workers); limited supply results in 22 % coverage.
• Non‑pharmaceutical interventions (NPIs): Hand hygiene, respiratory etiquette, mask use in crowded indoor settings, temporary school closures during severe seasons.
• Antiviral treatment: Oseltamivir for confirmed cases; prophylaxis for close contacts during outbreaks.
• Public‑health messaging: Culturally appropriate campaigns to improve vaccine confidence and encourage early self‑isolation.

10. Skills Development (AO2) & Evaluation (AO3)

10.1. AO2 – Data‑handling Tasks

1. Attack‑rate calculation (Africa):
   Formula: AR = (C / P) × 100 %
   Assumptions: Population = 1.3 billion; Cases = 0.4 million.
   Answer: AR = (0.4 × 10⁶ / 1.3 × 10⁹) × 100 ≈ 0.031 %.
2. Graph interpretation (Figure 2):
   • Which pandemic showed the steepest rise in deaths? – The 1918 H1N1 pandemic.
   • What does the post‑2020 dip suggest? – COVID‑19 control measures (mask‑wearing, reduced travel) suppressed influenza transmission, demonstrating interaction between concurrent pandemics.
3. Mapping exercise (Figure 1): Identify three regions with unusually high ILI rates in winter and suggest two geographical reasons for each.
   • Eastern Europe: (i) Cold, dry winter air; (ii) high urban density with extensive public‑transport networks.
   • East‑Asia (e.g., South Korea, Japan): (i) Temperate climate with sharp winter temperature drop; (ii) high school attendance rates and indoor heating that reduces humidity.
   • North‑America (Northeastern USA/Canada): (i) Low absolute humidity in winter; (ii) dense commuter corridors linking major cities.

10.2. AO3 – Evaluation Activity

Task: Evaluate the effectiveness of universal influenza vaccination in the United Kingdom compared with a targeted‑high‑risk approach in South Africa.

Evaluation criteria (use evidence from tables, maps and the case‑study notes):

• Coverage rates and equity – who receives the vaccine?
• Impact on hospitalisation and mortality statistics.
• Cost‑effectiveness – budget constraints, procurement, delivery.
• Feasibility of delivery in remote or informal settlements.
• Potential unintended consequences (e.g., vaccine hesitancy, strain‑selection pressure).

Write a concise paragraph (≈150 words) concluding which strategy is more appropriate for each country, supporting your judgement with the evidence above.

11. Scale Ladder – From Hour‑Scale to Global

Use this ladder to remind yourself which spatial and temporal scales are relevant when analysing influenza.

• Hour‑scale: Indoor humidity fluctuations over a school day affect droplet survival.
• Daily: School absenteeism data; local health‑clinic reports.
• Seasonal: National ILI surveillance (winter peak).
• Annual: National vaccination programme planning.
• Decadal: Monitoring antigenic drift and vaccine composition changes.
• Centennial / Global: Pandemic emergence, worldwide travel networks, WHO response.

12. Critical Note – Data Limitations

All figures are based on reported cases and deaths. In low‑income regions (e.g., parts of Africa and Nigeria) under‑reporting is common due to limited laboratory capacity and weak surveillance systems. Consequently, the true burden of influenza is likely higher than the numbers shown. When answering AO3 questions, acknowledge these uncertainties and discuss how they might affect policy decisions.

13. Suggested Revision Diagrams

• Flowchart of influenza transmission pathways and intervention points (source → droplet/aerosol → surface → host; vaccination & antivirals as break points).
• Systems diagram (Figure 3) with labelled inputs, processes, stores and outputs.
• World choropleth map of ILI rates (Figure 1) – colour‑coded by incidence.
• Time‑series graph of pandemic deaths (Figure 2) – log scale for easy comparison.
• Scale ladder (Section 11) – visual reminder of spatial‑temporal hierarchy.