function calculatePositivity() {
var totalTestsInput = document.getElementById('totalTests');
var positiveTestsInput = document.getElementById('positiveTests');
var resultBox = document.getElementById('resultBox');
var rateValueDisplay = document.getElementById('rateValue');
var rateStatusDisplay = document.getElementById('rateStatus');
var explanationText = document.getElementById('explanationText');
var errorMsg = document.getElementById('errorMsg');
// Reset display
errorMsg.style.display = 'none';
resultBox.style.display = 'none';
var total = parseFloat(totalTestsInput.value);
var positive = parseFloat(positiveTestsInput.value);
// Validation
if (isNaN(total) || isNaN(positive)) {
errorMsg.innerText = "Please enter valid numbers for both fields.";
errorMsg.style.display = 'block';
return;
}
if (total <= 0) {
errorMsg.innerText = "Total tests must be greater than zero.";
errorMsg.style.display = 'block';
return;
}
if (positive total) {
errorMsg.innerText = "Positive tests cannot exceed total tests performed.";
errorMsg.style.display = 'block';
return;
}
// Calculation
var rate = (positive / total) * 100;
var formattedRate = rate.toFixed(2);
// Display Logic
rateValueDisplay.innerText = formattedRate + "%";
// Remove old classes
rateStatusDisplay.classList.remove('status-good', 'status-moderate', 'status-high');
if (rate = 5 && rate < 10) {
rateStatusDisplay.innerText = "Moderate Transmission";
rateStatusDisplay.classList.add('status-moderate');
explanationText.innerText = "A rate between 5% and 10% suggests moderate community transmission. Increased testing and caution may be required.";
} else {
rateStatusDisplay.innerText = "High Transmission / Insufficient Testing";
rateStatusDisplay.classList.add('status-high');
explanationText.innerText = "A rate above 10% indicates widespread transmission or that not enough testing is being done to detect mild cases.";
}
resultBox.style.display = 'block';
}
How to Calculate COVID-19 Positivity Rate
The COVID-19 positivity rate (also known as the "percent positive") is a critical epidemiologic metric used by public health officials to understand the current severity of the pandemic in a specific area. It helps answer two main questions: how widespread is the infection, and is the current testing capacity sufficient?
The Positivity Rate Formula
The calculation for the positivity rate is straightforward. It represents the percentage of all tests performed that come back with a positive result for the virus.
Formula:
(Number of Positive Tests ÷ Total Number of Tests Performed) × 100 = Positivity Rate %
Example Calculation
Imagine a local health clinic has performed 5,000 tests over the last week. Out of those tests, 250 returned a positive result.
Step 1: Divide positive cases by total tests: 250 / 5000 = 0.05
Step 2: Multiply by 100 to get the percentage: 0.05 × 100 = 5%
In this example, the positivity rate is 5%.
Why Does the Positivity Rate Matter?
This metric provides context to the raw number of confirmed cases. A high number of cases might simply mean a country is testing a massive number of people. However, the positivity rate reveals the relationship between testing volume and infection spread.
Low Positivity Rate (Below 5%): According to the World Health Organization (WHO), a positivity rate under 5% for at least two weeks suggests that the outbreak is under control. It also implies that testing capacity is sufficient to catch mild or asymptomatic cases.
High Positivity Rate (Above 10-20%): A high rate typically indicates widespread community transmission. Crucially, it often suggests that the area is not doing enough testing. When the rate is high, it usually means only the people with the most severe symptoms are being tested, and many asymptomatic carriers are being missed.
Factors Influencing the Calculation
When calculating or analyzing this rate, data quality is paramount. Several factors can skew the results:
Duplicate Reporting: Sometimes the same person is tested multiple times. Different regions calculate "total tests" differently (tests vs. people).
Lag Times: There is often a delay between when a test is performed and when the result is reported. Comparing "tests performed today" with "results received today" can sometimes lead to inaccuracies if the backlog is significant.
Testing Criteria: If testing is restricted only to hospitalized patients, the positivity rate will be artificially high compared to a scenario where random surveillance testing is conducted.