From Zero to Routine Biosurveillance: A 7-Step Model for Integrating Public Health Laboratories into IDSR in a Resource-Constrained Setting
1
Health, United Kingdom Health Security Agency, Islamabad, Pakistan
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
BACKGROUND:
In many low- and middle-income countries (LMICs), laboratory data are poorly integrated into public health surveillance. In Pakistan, laboratory surveillance was not recognised as a routine surveillance function; diagnostic data were neither systematically reported nor used for early warning. Consequently, laboratory reporting into surveillance was essentially non-existent, falling short of basic requirements under the International Health Regulations (IHR)1
METHODS:
In 2025, a pragmatic 7-step model was introduced to establish routine laboratory surveillance data flow within the Integrated Disease Surveillance and Response (IDSR) system2. Laboratory mapping and initial assessments were conducted nationwide, with provinces progressing through the 7 steps at different stages based on readiness and capacity. A stepwise approach enabled incremental system development. An initial network of 40 laboratories was established in one province using defined criteria. A DHIS-2 module was selected and configured at no additional software cost, as commercial laboratory information management systems were financially unfeasible, while DHIS-2 offered a flexible, open-source platform already operational for surveillance. Laboratory staff were trained and were formally notified to report weekly. After analysis, data was shared with surveillance teams follwoing standard operating procedures. Following stabilisation, the network expanded to more than 80 laboratories, including private and tertiary facilities, reporting on 35 nationally prioritised diseases.
RESULTS:
Routine weekly laboratory reporting was established for the first time, with reporting completeness increasing from 0% to 84–88%. Beyond improved completeness, laboratories identified outbreak signals and clusters communicated to surveillance teams, enabling detection of events that would otherwise have been missed, including an early cholera signal.
CONCLUSIONS:
This 7-step model demonstrates how LMICs can operationalise routine laboratory surveillance within IDSR using existing digital platforms. By enabling laboratories to actively contribute to outbreak detection through an incremental and scalable approach, the model strengthens biosurveillance and IHR laboratory capacities3 and offers a transferable blueprint for resource-constrained settings.
In many low- and middle-income countries (LMICs), laboratory data are poorly integrated into public health surveillance. In Pakistan, laboratory surveillance was not recognised as a routine surveillance function; diagnostic data were neither systematically reported nor used for early warning. Consequently, laboratory reporting into surveillance was essentially non-existent, falling short of basic requirements under the International Health Regulations (IHR)1
METHODS:
In 2025, a pragmatic 7-step model was introduced to establish routine laboratory surveillance data flow within the Integrated Disease Surveillance and Response (IDSR) system2. Laboratory mapping and initial assessments were conducted nationwide, with provinces progressing through the 7 steps at different stages based on readiness and capacity. A stepwise approach enabled incremental system development. An initial network of 40 laboratories was established in one province using defined criteria. A DHIS-2 module was selected and configured at no additional software cost, as commercial laboratory information management systems were financially unfeasible, while DHIS-2 offered a flexible, open-source platform already operational for surveillance. Laboratory staff were trained and were formally notified to report weekly. After analysis, data was shared with surveillance teams follwoing standard operating procedures. Following stabilisation, the network expanded to more than 80 laboratories, including private and tertiary facilities, reporting on 35 nationally prioritised diseases.
RESULTS:
Routine weekly laboratory reporting was established for the first time, with reporting completeness increasing from 0% to 84–88%. Beyond improved completeness, laboratories identified outbreak signals and clusters communicated to surveillance teams, enabling detection of events that would otherwise have been missed, including an early cholera signal.
CONCLUSIONS:
This 7-step model demonstrates how LMICs can operationalise routine laboratory surveillance within IDSR using existing digital platforms. By enabling laboratories to actively contribute to outbreak detection through an incremental and scalable approach, the model strengthens biosurveillance and IHR laboratory capacities3 and offers a transferable blueprint for resource-constrained settings.
| eISSN: | 2654-1459 |
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