Skip to main content

Table 1 A comparison of multiplication factors (MFs) for salmonellosis in several countries

From: Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

Country

Underestimation MF

Primary study type

Study

Under-ascertainment MF

Primary study type

Study

Underreporting MF

Primary study type

Study

Austria

3

RTS

[75]

      

Austria

11

RTS

[76]

      

Belgium

1.9

RTS

[75]

      

Belgium

3.5

RTS

[76]

      

Bulgaria

271

RTS

[75]

      

Bulgaria

718.5

RTS

[76]

      

Croatia

30.6

RTS

[75]

      

Cyprus

71.2

RTS

[75]

      

Cyprus

173.2

RTS

[76]

      

Czech Republic

3

RTS

[75]

      

Czech Republic

28.9

RTS

[76]

      

Denmark

1.8

RTS

[75]

      

Denmark

4.4

RTS

[76]

      

Denmark

17

PRC

[9]

      

Denmark

NT UEinf: 325 (5-95% quartiles: 190–505)

Sero/MOD

[77]

      

Estonia

1.3

RTS

[75]

      

Estonia

16.9

RTS

[76]

      

Finland

0.6

RTS

[75]

      

Finland

0.4

RTS

[76]

      

France

8.3

RTS

[75]

   

S.entd. $ : Data1: 7.1(95% CI: 6.7-7.7)

CRS

[78]

Data2: 12.5 (95% CI: 11.1-14.3)

Data3: 2 (95% CI: 1.9-2.2)

Spp other than S.entd.& S.typh.

Data1: 12.5 (95% CI: 7.1-16.7)

Data2: 16.6 (95% CI: 10–25)

Data3: 2.0 (95% CI: 1.1-2.8)

France

26.9

RTS

[76]

      

Germany

1.8

RTS

[75]

      

Germany

9.8

RTS

[76]

      

Germany

6.7

PRC

[9]

      

Greece

97.7

RTS

[75]

   

1.75

MOD/RC

[79]

Greece

1228.5

RTS

[76]

      

Greece

51.45 (PERT: 3.2; 99.7)

BoD/CRS

[80]

      

Hungary

5.5

RTS

[75]

      

Hungary

66.8

RTS

[76]

      

Ireland

4.3

RTS

[75]

      

Ireland

5.4

RTS

[76]

      

Italy

13.1

RTS

[75]

      

Italy

71.7

RTS

[76]

      

Italy

17

PRC

[9]

      

Latvia

11.7

RTS

[75]

      

Latvia

44.3

RTS

[76]

      

Lithuania

10

RTS

[75]

      

Lithuania

59.1

RTS

[76]

      

Luxembourg

4.5

RTS

[76]

      

Malta

92.6

RTS

[75]

      

Malta

222.7

RTS

[76]

      

Poland

16.2

RTS

[75]

      

Poland

114.1

RTS

[76]

      

Poland

18

PRC

[9]

      

Portugal

378

RTS

[75]

      

Portugal

2082.9

RTS

[76]

      

Romania

332

RTS

[75]

      

Romania

349.9

RTS

[76]

      

Slovakia

3.5

RTS

[75]

      

Slovakia

53.2

RTS

[76]

      

Slovenia

10

RTS

[75]

      

Slovenia

40.3

RTS

[76]

      

Spain

103

RTS

[75]

      

Spain

214.2

RTS

[76]

   

NT: Data 1 = 2.0 (95% CI: 2.0 - 2.1)

CRS

[81]

Data 2 = 1.5 (95% CI: 1.4 - 1.5)

Sweden

0.5

RTS

[76]

      

Sweden

10

PRC

[9]

   

Data 1 =1.05, Data 2 =1.02

CRS

[82]

The Netherlands

7.7

RTS

[75]

      

The Netherlands

26.3 (ref)

RTS

[76]

      

The Netherlands

24.7 (5-95% quartiles: 5.2 - 64.7)

BRI/BoD

[57]

5.8 (5-95% quartiles: 0.8 - 25.6)

BRI

[57]

4.3 (5-95% quartiles: 2.5 - 6.5)

BRI

[57]

The Netherlands

14 (5-95% quartiles: 3.6 – 56)

CBS/BoD

[56]

6.5 (5-95% quartiles: 0.0 - 20)

CBS/BoD

[56]

   

The Netherlands

14.3

LAB

[62]

      

The Netherlands

20

PRC

[9]

      

United Kingdom

4.3

RTS

[75]

      

United Kingdom

7.3

RTS

[76]

      

United Kingdom

4.7 (95% CI : 1.2 - 18.2)

CBS

[47]

3.4 (95% CI: 0.4 - 32.2)

CBS

[47]

1.4 (95% CI: 0.6 - 3.3)

CBS

[47]

United Kingdom

3.2 (95% CI : 1.4 - 12.0)

CBS

[2]

GP only, 1.4 (95% CI: 0.7 - 2.8)

CBS

[2]

   

United Kingdom

40

PRC

[9]

      

United Kingdom

NT, UElab: 3.9

CBS/BoD

[55]

      

EU-27 (excl.Croatia)

57.5 (11–140)

RTS

[76]

      

Iceland

0.4

RTS

[75]

      

Norway

1.0 (ref)

RTS

[75]

      

Norway

1.2

RTS

[76]

      

Switzerland

7.1

RTS

[76]

      

USA

NT, UElab: BD 9.8, NBD 67.7, total 38.6

CBS/BoD

[49]

NT, BD 6.8, NBD 8.6

[49]

    

USA

NT, 38 (taken from [49])

BoD

[83]

NT, BD - 2.86 (PERT 1.96 – 5.26)

BoD

[84]

NT UN, 1

 

[84]

NBD – 5.56 (PERT 5–6.67)

Canada

13 - 37

PM

[85]

      

Australia

‡BD:1-2d: 11.39 (95% CrI: 8.49–16.36)

PM

[33]

‡BD: 1-2d: 10 (95% CrI: 7.1-14.3)

 

[33]

   

3-4d: 2.82 (95% CrI: 2.17–3.98)

  

3-4d: 2.3 (95% CrI: 1.9-3.2)

 

≥5d: 1.81 (95% CrI: 1.33–2.72)

  

≥5d: 1.5 (95% CrI: 1.1-2.2)

     

NBD: 1-2d 143.29 (95% CrI: 83.3–371)

NBD; 1-2d: 10 (95% CrI: 7.1-14.3)

3-4d 13.06 (95% CrI: 6.37–67.83)

3-4d: 2.3 (95% CrI: 1.9-3.2)

≥5d 3.93 (95% CrI: 2.10–11.92)

≥5d: 1.5 (95% CrI: 1.1-2.2)

Overall: 7 (95% CrI: 4–16)

Japan

74.0 (5-95% quartiles: 35.8, 140.7)

CBS

[50]

S.brae. Age <10 years: 1.2,

CBS

[48]

   

> = 10 years: 1.7, Overall:1.6,

  1. 1. This table lists all extracted or derived MFs (with variance shown as 95% CI, 95% CrI, PERT distribution (max, min, mode), or 5-95% quartiles where available) from relevant studies found during the extensive literature review. MFs give an estimation of the extent of UE (combined UA and UR), UA and UR for salmonellosis in a particular country; the higher the MF, the higher the proportion of cases not captured by the surveillance system. These MFs could be applied to official figures as reported by public health agencies to adjust for UE and give a new estimate of total symptomatic infections occurring in a population at a given time. Exceptions include; “UEinf” where the MF can adjust official figures from public health agencies and give a new estimate of total infections (both symptomatic and asymptomatic) occurring in a population at a given time, and “UElab” where the MF can adjust official laboratory figures of laboratory confirmed infections and give a new estimate of total infections (both symptomatic and asymptomatic) occurring in a population at a given time. MFs of UA and UR can be multiplied together to make one MF of UE.
  2. 2. Study types abbreviations: CBS: Community-based study, RTS: Returning traveller study, CRS: Capture-recapture study, PRC: Pyramid reconstruction model, BRI: Bayesian risk of infection model, BoD: Burden of disease calculation, Sero: Analysis of serology data, LAB: Analysis of laboratory surveillance, RC: Analysis of reporting completeness, PM: Probability model, OUT: Outbreak analysis, MOD: Modelling other. Symptoms abbreviations: NT: Non-typhoidal salmonellosis; NBD: Non-bloody diarrhoea; BD: Bloody diarrhoea; severity of diarrhoea (d = days). Salmonella species abbreviations: S.entd. : S. enteritidis; S.typh. : S.typhimurium; S.brae. : S.braenderup.Other abbreviations: UN: Under-notification of laboratory confirmed infection; GP only: cases attending GP surgeries (not hospitals) only; $ Estimates corrected by the positive predictive value of one data source where (unlike the other two sources) notifications are not validated by a systematic procedure; ‡ No. cases in the community for every 100 reported.
  3. 3. For CRS, a MF is given to correct for UR for each data source (i.e. MF for 'Data 1’ will estimate the underreporting in data source 1). For MFs estimated in the same RTS, one country will be listed as the reference country (i.e. 'ref’) and all other countries compared to this.
Back to article page

BMC Public Health

ISSN: 1471-2458

Contact us