Kenya’s president quotes incorrect Covid-19 data again
This article is more than 2 years old
In September 2020, Kenya’s president Uhuru Kenyatta was cautiously optimistic as he eased restrictions intended to slow the spread of the Covid-19 pandemic.
But just over a month later, the president’s upbeat tone was gone. The country had “experienced a reversal” and had a “new wave” of the deadly virus, he said in a national address on 4 November.
“When we made the [September] decision to re-open the country, our positivity rate had fallen from 13% in June of this year, to 7% in July, and to a low of 4% in September,” the president said.
The positivity rate is the number of positive cases calculated as a share of the number of people tested. If you test 100 people and 10 are positive, the positivity rate is 10%. (For a deeper discussion of the measure, see here.)
Covid-19 positivity rates in Kenya are calculated by the country’s health ministry. Since the outbreak began, the ministry has reported a seven-day positivity average in each week’s situation report.
Experts told us that weekly positivity averages were preferred as they had “less noise” than averages for each day or month.
In a recent report, Africa Check found that Kenyatta got the positivity rate for June wrong at least twice, in August and in September.
In June, available official data showed that the highest seven-day positivity rate was 8% in the last week of the month, and not 13%. The rate only hit 13% in the last week of July. (Note: Find out how we established this in our fact-check.)
The president was also off the mark with data for July, when the highest positivity rate was 13%.
To cross-check this, we also used the seven-day moving average and compared it with other international data.
Kenyatta was more accurate with his numbers for September, when the rate ranged from 4% to 6%.
Under World Health Organization guidelines, less than 5% of samples testing positive for at least two weeks is one indicator that could be used to decide if restrictions can be eased.
But several other factors also need to be considered, experts said. These include the level of testing, the number of Covid-19 patients admitted to hospitals and the number in critical care.
But just over a month later, the president’s upbeat tone was gone. The country had “experienced a reversal” and had a “new wave” of the deadly virus, he said in a national address on 4 November.
“When we made the [September] decision to re-open the country, our positivity rate had fallen from 13% in June of this year, to 7% in July, and to a low of 4% in September,” the president said.
The positivity rate is the number of positive cases calculated as a share of the number of people tested. If you test 100 people and 10 are positive, the positivity rate is 10%. (For a deeper discussion of the measure, see here.)
Covid-19 positivity rates in Kenya are calculated by the country’s health ministry. Since the outbreak began, the ministry has reported a seven-day positivity average in each week’s situation report.
Experts told us that weekly positivity averages were preferred as they had “less noise” than averages for each day or month.
International data
In a recent report, Africa Check found that Kenyatta got the positivity rate for June wrong at least twice, in August and in September.
In June, available official data showed that the highest seven-day positivity rate was 8% in the last week of the month, and not 13%. The rate only hit 13% in the last week of July. (Note: Find out how we established this in our fact-check.)
The president was also off the mark with data for July, when the highest positivity rate was 13%.
To cross-check this, we also used the seven-day moving average and compared it with other international data.
Kenyatta was more accurate with his numbers for September, when the rate ranged from 4% to 6%.
Easing Covid-19 restrictions
Under World Health Organization guidelines, less than 5% of samples testing positive for at least two weeks is one indicator that could be used to decide if restrictions can be eased.
But several other factors also need to be considered, experts said. These include the level of testing, the number of Covid-19 patients admitted to hospitals and the number in critical care.
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