Here’s a draft you can adapt:

Subject: Urgent follow-up: Heating repair needed at [your address]

Dear [Landlord’s name],

I’m writing to follow up on the heating issue at [your address], which I first reported to you on [date]. It has now been three weeks, and the heating is still not working.

I understand that repairs can take time, but with the weather getting colder, this has become a serious health and safety concern. I would appreciate your help in getting this resolved promptly.

Could you please arrange for a qualified technician to repair the heating by [specific date, e.g., Friday, December 8]? If that isn’t possible, please let me know by [date/time] and provide a firm date for the repair.

I want to keep this simple and avoid any conflict, but I’m sure you understand that working heating is essential. If I don’t hear from you by [date], I’ll need to consider the options available to me as a tenant.

Thank you for your attention to this. I look forward to hearing from you.

Best regards, [Your name] [Your phone number / email]

This keeps the tone polite and cooperative while making clear that the delay has gone on long enough and you expect action.

import { useEffect, useState } from "react";

/**
 * Debounces a changing value and returns the last value after the specified delay.
 * The timeout is cancelled when the component unmounts or when `value`/`delay` changes.
 */
export function useDebouncedValue<T>(value: T, delay: number): T {
  const [debouncedValue, setDebouncedValue] = useState<T>(value);

  useEffect(() => {
    const timeoutId = setTimeout(() => {
      setDebouncedValue(value);
    }, delay);

    // Cleanup clears the timeout on unmount and before the next effect runs
    return () => {
      clearTimeout(timeoutId);
    };
  }, [value, delay]);

  return debouncedValue;
}

Usage example

function SearchInput() {
  const [query, setQuery] = useState("");
  const debouncedQuery = useDebouncedValue(query, 300);

  useEffect(() => {
    if (debouncedQuery) {
      // Fetch search results
    }
  }, [debouncedQuery]);

  return (
    <input
      value={query}
      onChange={(e) => setQuery(e.target.value)}
      placeholder="Search..."
    />
  );
}

Assuming “99% accurate” means:

• True positive rate = 99% (if someone uses the drug, test is positive 99% of the time)

• True negative rate = 99% (if someone does not use, test is negative 99% of the time)

Let:

• (P(\text{use}) = 0.005)

• (P(\text{positive} \mid \text{use}) = 0.99)

• (P(\text{positive} \mid \text{non-use}) = 0.01)

Using Bayes’ theorem:

[ P(\text{use} \mid \text{positive}) = \frac{0.99 \times 0.005}{(0.99 \times 0.005) + (0.01 \times 0.995)} ]

[ = \frac{0.00495}{0.00495 + 0.00995} = \frac{0.00495}{0.0149} \approx 0.332 ]

So the probability they actually use the drug is about 33%.

Why the surprise? Because people focus on the test’s 99% accuracy and ignore the very low base rate: only 0.5% of people use the drug.

Out of 100,000 people:

• 500 use the drug → 495 true positives

• 99,500 do not use → 995 false positives

So among 1,490 positive tests, only 495 are true users:

[ \frac{495}{1490} \approx 33\% ]

Even a highly accurate test produces many false positives when the condition is rare. This is known as the base rate fallacy.