| Literature DB >> 34308188 |
Emmanuel Sindiyo1, Ruth Maganga2, Kate M Thomas3, Jackie Benschop4, Emmanuel Swai5, Gabriel Shirima1, Ruth N Zadoks2.
Abstract
BACKGROUND: With the growth, urbanisation, and changing consumption patterns of Tanzania's human population, new livestock production systems are emerging. Intensification of poultry production may result in opportunities and threats for food safety, such as improved awareness of biosecurity or increasing prevalence of foodborne pathogens including nontyphoidal Salmonella or Campylobacter spp. We conducted a semiquantitative analysis of poultry production systems in northern Tanzania, with emphasis on biosecurity, health management practices, and prevalence of foodborne pathogens, to gain insight into potential associations between intensification and food safety.Entities:
Year: 2018 PMID: 34308188 PMCID: PMC8279270 DOI: 10.24248/EAHRJ-D-18-00034
Source DB: PubMed Journal: East Afr Health Res J ISSN: 2520-5277
FIGURE 1.Examples of Poultry Production Systems at Different Levels of Intensification
Prevalence of Campylobacter spp. and Nontyphoidal Salmonella in Tanzanian Poultry Farms Across a Gradient of Intensification
| Pathogen | Farm Type | Farm Level Positive/Tested (%)[ | Bird Level Positive/Tested (%) | Boot Socks Positive/Tested (%) |
|---|---|---|---|---|
| Extensive | 2/6 | 5/55 (9.1) | NA | |
| Semi-intensive | 3/6 | 7/60 (6.7) | NA | |
| Intensive | 7/8 | 12/80 (15.0) | NA | |
| Broiler | 1/6 | 3/60 (5.0) | NA | |
| All | 13/26 (50) | 27/255 (10.6) | NA | |
| Nontyphoidal | Extensive | 0/10 | 0/90 (0.0) | 0/10 |
| Semi-intensive | 1/10 | 1/98 (1.0) | 1/10 | |
| Intensive | 2/10 | 3/99 (3.0) | 2/10 | |
| Broiler | 2/10 | 4/99 (4.0) | 2/10 | |
| All | 5/40 (12.5)[ | 8/386 (2.1) | 5/40 (12.5)[ |
Percentage only calculated for denominator values greater than 25.
In total, 6 of 40 farms were positive for Salmonella: 1 semi-intensive farm, 2 intensive farms, and 3 broiler farms (1 farm demonstrated positivity via cloacal swabs only, 1 farm via boot socks only, and 4 farms via both).
Abbreviations: NA, not applicable; spp., several species.
FIGURE 2.Map of Study Area Showing Campylobacter and Salmonella Status by Farm Type and Location
FIGURE 3.Association Between Farm Intensification and Biological and Physical Biosecurity in Poultry Production Systems in Arusha Urban District, Northern Tanzania
Use and Knowledge of Vaccines and Drugs on Tanzanian Poultry Farms Across a Gradient of Intensification
| Farm Type | Statistics | ||||||
|---|---|---|---|---|---|---|---|
| Topic | Total n | Broiler n | Intensive n | Semi-intensive n | Extensive n | Chi-square | |
| Vaccines | |||||||
| Gumboro | 1 | 0 | 1 | 0 | 0 | 3.1 | .38 |
| Newcastle disease | 20 | 0 | 5 | 7 | 8 | 15.2 | .002 |
| Pox | 13 | 6 | 5 | 2 | 0 | 10.4 | <.02 |
| Drugs | |||||||
| Antihelminthics | 20 | 7 | 6 | 4 | 3 | 4.0 | .26 |
| Antimicrobials | |||||||
| Routinely | 10 | 7 | 1 | 1 | 1 | 14.4 | .002 |
| Occasionally | 12 | 2 | 5 | 4 | 1 | 4.8 | .19 |
| When birds are sick | 16 | 1 | 4 | 5 | 6 | 5.8 | .12 |
| Traditional herbs | 8 | 1 | 2 | 0 | 5 | 8.8 | .03 |
| Drug choice based on | |||||||
| Personal experience | 9 | 4 | 2 | 3 | 0 | 5.0 | .17 |
| Drug seller's advice | 21 | 4 | 4 | 5 | 8 | 4.3 | .23 |
| Veterinary advice | 9 | 2 | 4 | 2 | 1 | 2.5 | .48 |
| Knowledge of | |||||||
| Antimicrobials in poultry feed | 4 | 2 | 1 | 1 | 0 | 2.2 | .53 |
| Residue impact on people | 17 | 5 | 4 | 4 | 4 | 0.3 | .99 |
| Withdrawal time | |||||||
| Aware | 17 | 7 | 5 | 3 | 3 | 4.4 | .22 |
| Abides | 9 | 3 | 3 | 1 | 2 | 1.6 | .66 |
Engagement of Poultry Farmers With Farmers Groups, Extension and Information Providers, and Vaccine Suppliers Across a Gradient of Farm Intensification in Northern Tanzania
| Farm Type | Statistics[ | ||||||
|---|---|---|---|---|---|---|---|
| Topic | Total n | Broiler n | Intensive n | Semi-intensive n | Extensive n | Chi-square | |
| Farm group membership[ | 32 | 6 | 10 | 8 | 8 | 5.0 | .17 |
| Farmer field school | 25 | 8 | 5 | 6 | 6 | 2.0 | .57 |
| Poultry association | 15 | 2 | 5 | 4 | 4 | 1.3 | .72 |
| Useful | 10 | 3 | 2 | 1 | 4 | 2.7 | .46 |
| Main extension provider | |||||||
| Government | 8 | 0 | 1 | 3 | 4 | 6.3 | .10 |
| Input supplier | 21 | 8 | 5 | 4 | 4 | 4.3 | .23 |
| Nongovernmental organisation | 1 | 0 | 1 | 0 | 0 | 3.1 | .38 |
| Information sources | |||||||
| Farmer field school | 8 | 1 | 1 | 2 | 1 | 0.7 | .88 |
| Input supplier | 5 | 1 | 1 | 2 | 1 | 0.7 | .88 |
| Social media | 5 | 1 | 1 | 3 | 3 | 2.5 | .48 |
| Colleagues | 22 | 7 | 7 | 3 | 5 | 4.4 | .22 |
| Vaccine provider | |||||||
| Government extension | 1 | 0 | 0 | 1 | 0 | 3.1 | .38 |
| Input supplier | 38 | 10 | 10 | 9 | 9 | 2.1 | .55 |
P values indicate significance of an association between farm type and engagement (yes/no) based on chi-square analysis.
Ten farmers were interviewed per farm type, and numbers indicate the farmers using the specified membership or service. Some farmers did not use any of the service providers listed, so numbers may not add up to 10 per farm type.