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Group A streptococcal cases and treatments during the COVID-19 pandemic: a rapid report

Description
This rapid report describes monthly changes in the recording of diagnoses and symptoms related to group A streptococcal infection and the prescribing of antibiotics used to treat group A streptococcal infection. The supporting weekly report is linked below. A full description of the methods and results can be found in the published paper linked below.
Authors
Christine Cunningham, Louis Fisher, Christopher Wood, The OpenSAFELY Collaborative, Victoria Speed, Andrew D Brown, Helen J Curtis, Rose Higgins, Richard Croker, Ben FC Butler-Cole, David Evans, Peter Inglesby, Iain Dillingham, Sebastian CJ Bacon, Elizabeth Beech, Kieran Hand, Simon Davy, Tom Ward, George Hickman, Lucy Bridges, Thomas O’Dwyer, Steven Maude, Rebecca M Smith, Amir Mehrkar, Liam C Hart, Chris Bates, Jonathan Cockburn, John Parry, Frank Hester, Sam Harper, Ben Goldacre, Brian MacKenna
Contact
Get in touch and tell us how you use this report or new features you'd like to see: team@opensafely.org
First published
25 Jan 2023
Last released
19 Apr 2023
Links

Group A streptococcal cases and treatments during the COVID-19 pandemic: a rapid report

01-01-2018 through 31-03-2023 by month

Background

During the COVID-19 pandemic there has been a substantial change to the pattern of circulating viruses and bacteria that cause illnesses. In order to support ongoing response and recovery of NHS services from the COVID-19 pandemic, it is useful to have detailed information on patterns of disease being reported by the NHS and on treatments such as antibiotics.

In the winter of 22/23 UKHSA (December 8th) reported an unseasonal increase of scarlet fever and group A streptococcus infections. Sadly, between 19th September 2022 and 26th March 2023 there have been 355 deaths in England across all age groups, including 40 children under 18. UKHSA indicates that the increase is likely to reflect increased susceptibility to these infections in children due to low numbers of cases during the COVID-19 pandemic, along with current circulation of respiratory viruses. As of March 26th 2023, scarlet fever notifications have returned to expected levels, but invasive group A strep notifications remain higher than normal.

This rapid report describes changes in the recording of diagnoses and symptoms related to group A streptococcal infection and the prescribing of antibiotics used to treat group A streptococcal infection. We will routinely update the data in this report and invite anyone who finds it useful to get in touch and tell us how you use this report or new features you'd like to see.

Methods

This study used data from OpenSAFELY-TPP, which covers 40% of the population of England. For a description of the representativeness of this sample, please see our manuscript here. Individuals were included if they were alive and registered at a TPP practice each month, across the study period. Patients were excluded if their listed age was not between 0 and 120 years.

Counts represent patients with at least one prescription or clinical event in that month. Patients with more than one of the same prescription or clinical event in a month were only counted once. Rates divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.

Counts <=5 have been redacted and all numbers rounded to the nearest 10 to avoid potential re-identification of individuals. The rates displayed were computed with these rounded counts.

Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol.

Clinical events data is based on a clinical code being added to a patient's record. This is often added by a clinician during a consultation to indicate the presence of a sign/symptom (e.g. sore throat) or that a clinical diagnosis has been made (e.g. Scarlet Fever). These codes do not necessarily indicate positive test results.

Links to the codelist for each analysis can be found beneath the relevant section.

Antibiotic Prescribing

The below charts show the count and rate of patients prescribed the following antibiotics each month: phenoxymethylpenicillin, amoxicillin, clarithromycin, erythromycin, azithromycin, flucloxacillin, cefalexin and co-amoxiclav. This is based on the antibiotic recommendation given in NHS England Group A streptococcus in children: Interim clinical guidance summary 22nd December 2022.

Any antibiotic

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The below charts show the count of patients prescribed any of the above listed antibiotics each month, followed by a table with the underlying counts and a chart with of the rate of prescribing with the years stacked on top of each other.

Date Patient Count Amoxicillin Azithromycin Cefalexin Clarithromycin Co Amoxiclav Erythromycin Flucloxacillin Phenoxymethylpenicillin
01-01-18 23816470 416960 19640 22480 100210 49550 34170 114030 83330
01-02-18 23864720 300380 18180 19390 75850 41160 29350 103560 80640
01-03-18 23900720 280150 18790 20280 75070 42680 30210 113600 91710
01-04-18 23930720 222280 17960 19600 65180 39560 26280 116640 73930
01-05-18 23973370 207280 18100 19760 63360 39520 26420 130090 73160
01-06-18 24004950 172180 17090 19090 57550 37960 23710 138260 63280
01-07-18 24028930 163050 17500 19480 58640 39180 23700 157020 59880
01-08-18 24069930 149250 17550 19910 54480 39620 21260 143940 47070
01-09-18 24103990 186510 17400 18670 55320 36760 20670 118510 46970
01-10-18 24138420 258180 19930 20600 68020 42050 24850 125970 58770
01-11-18 24193720 271100 19810 19870 67060 39460 24700 114280 61830
01-12-18 24223360 308020 19680 19640 71880 38660 23940 99450 64690
01-01-19 24239080 353770 20550 20910 85390 42970 25640 111760 74340
01-02-19 24282590 282780 19080 18580 71530 37220 23090 102010 69230
01-03-19 24304780 243360 19440 19500 66660 38070 22780 111500 72420
01-04-19 24326150 228950 19250 19300 64150 36780 21790 110860 66140
01-05-19 24354350 191700 19130 19540 60190 36970 20630 118040 62050
01-06-19 24378970 165500 17580 18480 53700 34040 18520 116740 57390
01-07-19 24409790 172840 19010 20540 61320 38420 21390 156740 64550
01-08-19 24447460 145420 18360 19890 53540 36020 18200 139230 48460
01-09-19 24474940 183170 19270 20080 56310 36160 18710 125550 53510
01-10-19 24508740 256750 20820 20900 68210 39260 21440 121160 64220
01-11-19 24567720 273550 20700 19960 68330 37000 21460 108670 68610
01-12-19 24600400 357470 21650 20770 80460 39440 24050 102850 79380
01-01-20 24613110 312320 21620 21680 81390 41320 22280 114250 77790
01-02-20 24653160 241590 20350 19420 66060 35400 20000 102790 76330
01-03-20 24680540 266050 24410 22400 74980 42100 22240 110640 85420
01-04-20 24700320 151040 20980 21700 54020 40870 15750 109330 48000
01-05-20 24691700 96550 19460 20040 41110 34990 13490 111480 36960
01-06-20 24692400 93450 19750 21250 41550 36340 14120 129730 37680
01-07-20 24699260 92820 19660 21980 42060 36630 14480 131480 39720
01-08-20 24716720 86770 18540 19810 38640 32270 13290 126550 35840
01-09-20 24726330 141780 20840 22700 48720 36810 15990 129020 54720
01-10-20 24742820 135860 20770 22870 46090 36680 14930 114630 43760
01-11-20 24775380 125070 21260 22790 44200 36610 14410 111050 43390
01-12-20 24799370 133120 21510 23370 45100 37440 14370 109180 45400
01-01-21 24814170 123690 20580 21860 42040 35240 13320 100780 38800
01-02-21 24834870 102390 19520 21200 38020 32760 12710 102430 36100
01-03-21 24861590 121780 20830 23980 44550 36200 14810 124900 45770
01-04-21 24911500 116910 19280 21440 40520 32030 13760 110080 41010
01-05-21 24945240 138980 18580 20800 41940 31520 14760 101610 49240
01-06-21 24979400 167280 19450 22450 49330 35450 16730 129950 52670
01-07-21 25017380 163120 19000 22670 50280 36120 16270 138770 52670
01-08-21 25052200 147590 18930 22990 46870 34960 14420 123260 48840
01-09-21 25077030 210110 19980 23920 56760 37050 16770 126360 66940
01-10-21 25109010 277710 20160 23790 63310 37460 18210 110850 70510
01-11-21 25150630 286220 21140 24760 67540 38750 18680 111900 76910
01-12-21 25189030 284560 21410 24790 66690 39220 18100 104750 79400
01-01-22 25212560 196200 20860 23910 54180 35510 14550 102790 66420
01-02-22 25243710 178260 19740 22510 50380 33480 14400 100980 67480
01-03-22 25260560 233630 21020 25050 62730 38940 17250 118120 85300
01-04-22 25276230 201470 19540 22600 54420 34200 14770 102130 70030
01-05-22 25289780 196170 20050 24050 56920 36840 15750 119490 81150
01-06-22 25316240 186530 19180 23100 55580 34620 15390 119080 80410
01-07-22 25335660 184360 19190 23270 57320 35270 15760 132390 85340
01-08-22 25351060 151750 19570 25400 52980 36700 13950 138380 66420
01-09-22 25382020 183320 20310 25390 53420 36060 13720 119860 67980
01-10-22 25405980 268030 20740 25650 64910 37240 16200 111150 82690
01-11-22 25458380 320560 21450 26600 73880 38960 19190 113140 103660
01-12-22 25494320 558480 26390 31650 124680 47980 43250 104600 193910
01-01-23 25500600 346410 22660 28240 82650 43480 20600 111800 116470
01-02-23 25529380 279330 20730 25220 68960 38570 16920 106060 107730
01-03-23 25541940 289660 22270 27800 74550 43040 18990 121050 119540

The below charts show the monthly count and rate of patients with any of the listed antibiotics across the study period, with a breakdown by key demographic subgroups.

Count
Rate

Phenoxymethylpenicillin (Codelist)

The below charts show patients prescribed phenoxymethylpenicillin between 01-01-2018 and 31-03-2023. The codelist used to identify phenoxymethylpenicillin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the phenoxymethylpenicillin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501011P0AAAJAJ Phenoxymethylpenicillin 250mg tablets 3,087,360 72.40
0501011P0AAAFAF Phenoxymethylpenicillin 250mg/5ml oral solution 487,610 11.44
0501011P0AAADAD Phenoxymethylpenicillin 125mg/5ml oral solution 486,430 11.41
0501011P0AAASAS Phenoxymethylpenicillin 250mg/5ml oral solution sugar free 109,570 2.57
0501011P0AAARAR Phenoxymethylpenicillin 125mg/5ml oral solution sugar free 93,050 2.18

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded phenoxymethylpenicillin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded phenoxymethylpenicillin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Amoxicillin (Codelist)

The below charts show patients prescribed amoxicillin between 01-01-2018 and 31-03-2023. The codelist used to identify amoxicillin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the amoxicillin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501013B0AAABAB Amoxicillin 500mg capsules 9,815,420 72.27
0501013B0AAATAT Amoxicillin 250mg/5ml oral suspension sugar free 2,083,150 15.34
0501013B0AAASAS Amoxicillin 125mg/5ml oral suspension sugar free 530,600 3.91
0501013B0AAAKAK Amoxicillin 250mg/5ml oral suspension 500,130 3.68
0501013B0BCABAB Amoxil 500mg capsules 269,790 1.99

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded amoxicillin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded amoxicillin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Clarithromycin (Codelist)

The below charts show patients prescribed clarithromycin between 01-01-2018 and 31-03-2023. The codelist used to identify clarithromycin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the clarithromycin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501050B0AAADAD Clarithromycin 500mg tablets 2,932,780 76.74
0501050B0AAAAAA Clarithromycin 250mg tablets 347,220 9.09
0501050B0AAABAB Clarithromycin 125mg/5ml oral suspension 295,830 7.74
0501050B0AAAHAH Clarithromycin 250mg/5ml oral suspension 230,940 6.04
0501050B0AAAEAE Clarithromycin 500mg modified-release tablets 12,680 0.33

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded clarithromycin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded clarithromycin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Erythromycin (Codelist)

The below charts show patients prescribed erythromycin between 01-01-2018 and 31-03-2023. The codelist used to identify erythromycin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the erythromycin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501050C0AAABAB Erythromycin 250mg gastro-resistant tablets 811,350 66.42
0501050H0AAAMAM Erythromycin ethyl succinate 250mg/5ml oral suspension sugar free 145,390 11.90
0501050H0AAALAL Erythromycin ethyl succinate 125mg/5ml oral suspension sugar free 80,210 6.57
0501050H0AAABAB Erythromycin ethyl succinate 250mg/5ml oral suspension 77,880 6.38
0501050H0AAAAAA Erythromycin ethyl succinate 125mg/5ml oral suspension 52,530 4.30

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded erythromycin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded erythromycin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Azithromycin (Codelist)

The below charts show patients prescribed azithromycin between 01-01-2018 and 31-03-2023. The codelist used to identify azithromycin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the azithromycin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501050A0AAAGAG Azithromycin 250mg tablets 756,900 60.15
0501050A0AAADAD Azithromycin 500mg tablets 239,680 19.05
0501050A0AAABAB Azithromycin 200mg/5ml oral suspension 136,660 10.86
0501050A0AAAAAA Azithromycin 250mg capsules 120,640 9.59
0501050A0BBABAB Zithromax 200mg/5ml oral suspension 2,110 0.17

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded azithromycin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded azithromycin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Flucloxacillin (Codelist)

The below charts show patients prescribed flucloxacillin between 01-01-2018 and 31-03-2023. The codelist used to identify flucloxacillin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the flucloxacillin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501012G0AAABAB Flucloxacillin 500mg capsules 6,268,930 84.63
0501012G0AAAAAA Flucloxacillin 250mg capsules 394,340 5.32
0501012G0AAAFAF Flucloxacillin 125mg/5ml oral solution 368,230 4.97
0501012G0AAAGAG Flucloxacillin 250mg/5ml oral solution 219,690 2.97
0501012G0AAAQAQ Flucloxacillin 250mg/5ml oral solution sugar free 118,900 1.61

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded flucloxacillin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded flucloxacillin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Cefalexin (Codelist)

The below charts show patients prescribed cefalexin between 01-01-2018 and 31-03-2023. The codelist used to identify cefalexin is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the cefalexin codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501021L0AAABAB Cefalexin 500mg capsules 633,860 45.53
0501021L0AAAAAA Cefalexin 250mg capsules 344,980 24.78
0501021L0AAAGAG Cefalexin 250mg tablets 158,380 11.38
0501021L0AAAHAH Cefalexin 500mg tablets 87,240 6.27
0501021L0AAADAD Cefalexin 250mg/5ml oral suspension 64,650 4.64

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded cefalexin events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded cefalexin prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Co-Amoxiclav (Codelist)

The below charts show patients prescribed co-amoxiclav between 01-01-2018 and 31-03-2023. The codelist used to identify co-amoxiclav is here.

Counts: represent patients with at least one prescription event in that month. Patients with more than one of the same prescription in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Prescribing data is based on prescriptions issued within the Electronic Health Record. Prescriptions may not always be dispensed or in some cases the dispensed item may differ from the prescribed item due to the use of a Serious Shortage Protocol

The following table shows the top 5 used codes within the co-amoxiclav codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
0501013K0AAAJAJ Co-amoxiclav 500mg/125mg tablets 1,929,100 80.92
0501013K0AAAAAA Co-amoxiclav 250mg/125mg tablets 181,280 7.60
0501013K0AAAGAG Co-amoxiclav 250mg/62mg/5ml oral suspension sugar free 125,590 5.27
0501013K0AAADAD Co-amoxiclav 125mg/31mg/5ml oral suspension sugar free 66,370 2.78
0501013K0AAAIAI Co-amoxiclav 250mg/62mg/5ml oral suspension 33,020 1.39

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded co-amoxiclav events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with a group A strep clinical event of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with a recorded co-amoxiclav prescription event AND a record of any of the potential group A strep clinical events of interest (scarlet fever, sore throat/tonsillitis or invasive group A strep) up to 14 days prior to or 7 days after the prescription event.

Recorded Clinical Events

The below charts show the count and rate of patients with a recording of the following clincial events each month: scarlet fever, sore throat/tonsillitis and invasive strep A.

Any clinical

Counts: represent patients with at least one clinical event in that month. Patients with more than one of the same clinical event in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Clinical events data is based on a clinical code being added to a patient's record. This is often added by a clinician during a consultation to indicate the presence of a sign/symptom (e.g. sore throat) or that a clinical diagnosis has been made (e.g. Scarlet Fever). These codes do not necessarily indicate positive test results.

The below charts show the count of patients with any of the above listed clinical events each month, followed by a table with the underlying counts and a chart with the rate of clinical events with the years stacked on top of each other.

Date Patient Count Invasive Strep A Scarlet Fever Sore Throat Tonsillitis
01-01-18 23816470 20 1900 91510
01-02-18 23864720 30 3080 83620
01-03-18 23900720 30 4570 89300
01-04-18 23930720 30 2670 69820
01-05-18 23973370 20 2000 70380
01-06-18 24004950 10 1090 59630
01-07-18 24028930 20 680 54550
01-08-18 24069930 10 320 40130
01-09-18 24103990 10 330 43980
01-10-18 24138420 10 610 55280
01-11-18 24193720 10 820 59500
01-12-18 24223360 10 880 63360
01-01-19 24239080 20 960 75070
01-02-19 24282590 20 1130 68640
01-03-19 24304780 20 1240 70980
01-04-19 24326150 10 940 62050
01-05-19 24354350 20 680 57470
01-06-19 24378970 10 640 52440
01-07-19 24409790 20 660 58040
01-08-19 24447460 10 260 41000
01-09-19 24474940 10 300 49080
01-10-19 24508740 20 670 60540
01-11-19 24567720 10 950 65270
01-12-19 24600400 20 1510 77470
01-01-20 24613110 20 1120 73550
01-02-20 24653160 10 1600 72260
01-03-20 24680540 20 1330 59970
01-04-20 24700320 10 120 21950
01-05-20 24691700 20 50 16170
01-06-20 24692400 10 60 16610
01-07-20 24699260 10 60 18290
01-08-20 24716720 [REDACTED] 50 17280
01-09-20 24726330 [REDACTED] 90 30860
01-10-20 24742820 [REDACTED] 70 21700
01-11-20 24775380 [REDACTED] 80 20710
01-12-20 24799370 [REDACTED] 100 21670
01-01-21 24814170 [REDACTED] 70 17280
01-02-21 24834870 10 70 15940
01-03-21 24861590 [REDACTED] 110 22250
01-04-21 24911500 10 100 20190
01-05-21 24945240 [REDACTED] 130 28330
01-06-21 24979400 [REDACTED] 150 30530
01-07-21 25017380 [REDACTED] 140 29950
01-08-21 25052200 [REDACTED] 100 27250
01-09-21 25077030 [REDACTED] 170 41540
01-10-21 25109010 10 280 45250
01-11-21 25150630 [REDACTED] 320 49670
01-12-21 25189030 10 330 49570
01-01-22 25212560 [REDACTED] 350 41210
01-02-22 25243710 10 520 42210
01-03-22 25260560 20 1360 54760
01-04-22 25276230 20 1180 44030
01-05-22 25289780 20 1720 53270
01-06-22 25316240 10 1540 54400
01-07-22 25335660 30 1580 58630
01-08-22 25351060 40 530 42130
01-09-22 25382020 20 610 43880
01-10-22 25405980 20 1430 55000
01-11-22 25458380 50 2710 71420
01-12-22 25494320 140 13040 135860
01-01-23 25500600 90 3830 84750
01-02-23 25529380 70 3240 76250
01-03-23 25541940 70 3650 83080

The below charts show the monthly count and rate of patients with any of the listed clinical events across the study period, with a breakdown by key demographic subgroups.

Count
Rate

Scarlet Fever (Codelist)

The below charts show patients with recorded events of scarlet fever between 01-01-2018 and 31-03-2023. The codelist used to identify scarlet fever is here.

Counts: represent patients with at least one clinical event in that month. Patients with more than one of the same clinical event in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Clinical events data is based on a clinical code being added to a patient's record. This is often added by a clinician during a consultation to indicate the presence of a sign/symptom (e.g. sore throat) or that a clinical diagnosis has been made (e.g. Scarlet Fever). These codes do not necessarily indicate positive test results.

The following table shows the 5 most used codes within the scarlet fever codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
30242009 Scarlet fever 60,460 82.98
1087781000000109 Suspected scarlet fever 7,970 10.94
170523002 Notification of scarlet fever 3,210 4.41
186357007 Streptococcal sore throat with scarlatina 1,130 1.55
Other - 90 0.12

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded scarlet fever events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with an antibiotic of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with recorded scarlet fever events AND a prescription for any antibiotic listed in this report up to 7 days prior to or 14 days after the clinical event.

Sore Throat/Tonsillitis (Codelist)

The below charts show patients with recorded events of sore throat/tonsillitis between 01-01-2018 and 31-03-2023. The codelist used to identify sore throat/tonsillitis is here.

Counts: represent patients with at least one clinical event in that month. Patients with more than one of the same clinical event in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Clinical events data is based on a clinical code being added to a patient's record. This is often added by a clinician during a consultation to indicate the presence of a sign/symptom (e.g. sore throat) or that a clinical diagnosis has been made (e.g. Scarlet Fever). These codes do not necessarily indicate positive test results.

The following table shows the 5 most used codes within the sore throat/tonsillitis codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
90176007 Tonsillitis 1,436,220 44.48
267102003 Sore throat symptom 552,530 17.11
162397003 Pain in throat 454,370 14.07
17741008 Acute tonsillitis 367,800 11.39
405737000 Pharyngitis 234,240 7.25

The second chart illustrates top code usage over time. Codes that were in the top 5 either in the first or last month of the study period were included.

The below charts show the monthly count and rate of patients with recorded sore throat/tonsillitis events across the study period, with a breakdown by key demographic subgroups.

Count
Rate
Rate with an antibiotic of interest

The below chart shows the monthly rate, broken down by key demographic subgroups, of patients with recorded sore throat/tonsillitis events AND a prescription for any antibiotic listed in this report up to 7 days prior to or 14 days after the clinical event.

Invasive Strep A (Codelist)

The below charts show patients with recorded events of invasive strep a between 01-01-2018 and 31-03-2023. The codelist used to identify invasive strep a is here.

Counts: represent patients with at least one clinical event in that month. Patients with more than one of the same clinical event in a month were only counted once. Counts <=5 were redacted and all numbers were rounded to the nearest 10.
Rates: divide the count by the included study population and multiply by 1,000 to achieve a rate per 1,000 registered patients.
Note: Clinical events data is based on a clinical code being added to a patient's record. This is often added by a clinician during a consultation to indicate the presence of a sign/symptom (e.g. sore throat) or that a clinical diagnosis has been made (e.g. Scarlet Fever). These codes do not necessarily indicate positive test results.

The following table shows the 5 most used codes within the invasive strep a codelist after summing code usage over the entire study period. Codes with low usage that would have been redacted have been grouped into the category 'Other'. The proportion was computed after rounding. If more than 5 codes in the codelist are used, the proportion will not add up to 100%.

Code Description Count of patients with code Proportion of total patients with code (%)
449504009 Sepsis caused by Streptococcus pyogenes 540 43.90
406614006 Invasive Group A beta-hemolytic streptococcal disease 320 26.02
Other - 190 15.45
1087891000000103 Suspected invasive Group A beta-haemolytic streptococcal disease 180 14.63