ONE area of Gwent is the most likely place in Wales to become a Covid-19 hotspot in the next few weeks, scientists have predicted.
Scientists at Imperial College London believe Caerphilly has a chance of becoming a coronavirus hotspot by mid-March.
The data has been produced by the Medical Research Council Centre for Global Infectious Disease Analysis at Imperial College, in conjunction with its mathematics department.
It predicts the probability of local authorities recording at least 100 cases per 100,000 people over the coming weeks and becoming a 'hotspot' on its map.
They give Caerphilly a 26 per cent chance of becoming a hotspot by next week (March 7 to March 13).
Newport has the next highest risk in Gwent, but that sits at just eight per cent.
The data can also be used to predict how likely areas are to see coronavirus rates in excess of 50 cases per 100,000 people, the barometer that was used to trigger local lockdowns in Wales in September.
Caerphilly is more likely to exceed that number than not according to the map, which gives the borough a 59 per cent chance of having more than 50 cases per 100,000.
Again Newport is the second highest in Gwent, with a 42 per cent chance.
Torfaen has a 28 per cent chance, Blaenau Gwent a 17 per cent chance, and Monmouthshire a 13 per cent chance.
The positive news from the map, is that it is confident in predicting decreasing case numbers in four of Gwent's five local authority areas.
The number of new infections in Monmouthshire, Torfaen and Blaenau Gwent are all decreasing according to Imperial College, while the numbers in Newport are "likely decreasing".
However, the direction in Caerphilly is "unclear".
The probability of new infections increasing in the borough is given as 35 per cent, the joint highest in Wales.
In Newport that is 13 per cent, it is nine per cent in Blaenau Gwent, six per cent in Monmouthshire, and five per cent in Torfaen.
Imperial College states that its projections for hotspots assume no change in interventions and human behaviour has been made since a week before the last observed data.
Imperial College also lists a number of limitations to its predictions.
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It explains: "Predictions on this page assume no change in current interventions (lockdowns, school closures, and others) in the local area beyond those already taken about a week before the end of observations.
"An increase in cases in an area can be due to an increase in testing. The model currently does not account for this.
"Each area (local authority) is treated independently apart from the overall Rt estimate for its region. Thus the epidemic in a region is neither affected by nor affects any other region. It also does not include importations from other countries.
"The population within an area is considered to be homogeneous - i.e. all individuals are considered equally likely to be affected by the disease progression."
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