UPSC MainsMANAGEMENT-PAPER-I202015 Marks
Q8.

Question 8

A State Public Health Department has allocated ₹40,00,000 for advertising information on Coronavirus pandemic. Two types of advertisements will be used: Radio and Newspaper. Each radio advertisement costs ₹20,000 and reaches an estimated 3000 people. Each newspaper advertisement costs ₹50,000 and reaches an estimated 7000 people. In planning the advertising campaign, the Public Health Department would like to reach as many people as possible, but they have decided that at least 10 advertisements of each type must be used. How many advertisements of each type should be used ? How many people will this reach? Find the optimal solution that best satisfies all requirements.

How to Approach

This question is a linear programming problem disguised within a public health context. The approach involves formulating the problem mathematically, defining variables, setting up the objective function (maximizing reach), and establishing constraints (budget and minimum advertisements). Solving this can be done through algebraic methods or, more efficiently, using optimization techniques. The answer should clearly define the variables, formulate the equations, solve for the optimal number of advertisements, and calculate the total reach.

Model Answer

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Introduction

Public health campaigns often face the challenge of maximizing impact with limited resources. Effective advertising is crucial for disseminating vital information, particularly during public health crises like pandemics. The allocation of funds across different advertising channels requires careful consideration to reach the largest possible audience. This problem exemplifies a common operational research scenario where optimization techniques are employed to achieve the best possible outcome given specific constraints. This question tests the ability to apply mathematical modeling to a real-world administrative problem, a skill valuable for effective public health management.

Problem Formulation

Let:

  • x = the number of radio advertisements
  • y = the number of newspaper advertisements

Objective Function: Maximize the total reach (Z)

Z = 3000x + 7000y

Constraints:

  • Budget Constraint: 20000x + 50000y ≤ 4000000
  • Minimum Radio Advertisements: x ≥ 10
  • Minimum Newspaper Advertisements: y ≥ 10
  • Non-negativity Constraint: x, y ≥ 0 (implied, but good practice to state)

Simplifying the Budget Constraint

The budget constraint can be simplified by dividing by 10000:

2x + 5y ≤ 400

Graphical Solution (or Algebraic Approach)

We can solve this problem graphically or algebraically. Let's use an algebraic approach combined with understanding the feasible region.

Finding Corner Points of the Feasible Region

The feasible region is defined by the constraints. We need to find the corner points of this region.

  • Intersection of x = 10 and y = 10: (10, 10)
  • Intersection of x = 10 and 2x + 5y = 400: 2(10) + 5y = 400 => 5y = 380 => y = 76. So, (10, 76)
  • Intersection of y = 10 and 2x + 5y = 400: 2x + 5(10) = 400 => 2x = 350 => x = 175. So, (175, 10)

Evaluating the Objective Function at Corner Points

Now, we evaluate the objective function Z = 3000x + 7000y at each corner point:

  • Z(10, 10) = 3000(10) + 7000(10) = 30000 + 70000 = 100000
  • Z(10, 76) = 3000(10) + 7000(76) = 30000 + 532000 = 562000
  • Z(175, 10) = 3000(175) + 7000(10) = 525000 + 70000 = 595000

Optimal Solution

The maximum reach (Z) is 595000, which occurs when x = 175 and y = 10.

Total Reach

Therefore, the Public Health Department should use 175 radio advertisements and 10 newspaper advertisements to reach the maximum number of people, which is 595,000.

Conclusion

In conclusion, by employing a linear programming approach, the State Public Health Department can optimize its advertising campaign for the Coronavirus pandemic. The optimal strategy involves allocating resources towards 175 radio advertisements and 10 newspaper advertisements, resulting in a reach of 595,000 people. This demonstrates the power of quantitative methods in public health decision-making, ensuring efficient resource utilization and maximizing the impact of crucial information dissemination. Further analysis could consider factors like demographic targeting and advertisement effectiveness to refine the campaign even further.

Answer Length

This is a comprehensive model answer for learning purposes and may exceed the word limit. In the exam, always adhere to the prescribed word count.

Additional Resources

Key Definitions

Linear Programming
A mathematical method for achieving the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.
Objective Function
In mathematical optimization, the objective function is the function that you want to maximize or minimize. It represents the goal of the optimization problem.

Key Statistics

According to the World Health Organization (WHO), effective risk communication and community engagement are crucial for pandemic preparedness and response. Approximately 60-80% of the effectiveness of a public health intervention relies on effective communication.

Source: WHO, 2023 (Knowledge Cutoff: 2023)

A study by Nielsen in 2020 showed that during the initial phase of the COVID-19 pandemic, radio listenership increased by 15% in the United States, highlighting its continued relevance as a medium for reaching a broad audience.

Source: Nielsen, 2020 (Knowledge Cutoff: 2023)

Examples

Pulse Polio Campaign

India's Pulse Polio campaign, launched in 1985, successfully utilized mass media advertising (radio, television, newspapers) alongside door-to-door vaccination to eradicate polio. The campaign’s success hinged on effective communication and reaching every segment of the population.

Frequently Asked Questions

What if the minimum advertisement requirements were higher?

Increasing the minimum advertisement requirements would shrink the feasible region, potentially reducing the maximum reach. The optimal solution might shift, and the maximum reach could be lower than the current solution.