Assessment of Cold Chain Infrastructure and Vaccine Logistics Before and After eVIN Implementation at Cold Chain Points in Indore District: An Observational Study (2014–2021)

Abstract

Background:

The Electronic Vaccine Intelligence Network (eVIN) was introduced in India to strengthen vaccine logistics through digitization and real-time stock and temperature monitoring. The present study assessed the cold chain infrastructure and vaccine logistics before and after eVIN implementation at cold chain points (CCPs) in Indore district.

Material and Methods:

A pre–post observational study was conducted at all functional CCPs of Indore district. Post-eVIN assessment (2020–2021) included 40 CCPs, while pre-eVIN data (2014–2015) from 36 CCPs were obtained from program records. A census approach was used. Data were collected using standardized supportive supervision checklists and secondary databases. Data were analyzed using descriptive statistics and expressed as frequencies and percentages.

Results:

Higher compliance was observed in various cold chain parameters in post-eVIN period. Most cold chain equipment were functional during assessment. Availability of functional power back-up increased from 22.2% to 72.5%. CCPs maintaining updated stock and distribution registers increased from 72.2% to 100%. The presence of functional thermometers increased from 83.3% to 90%. Real-time web-based documentation was implemented at all CCPs post-eVIN. Adequate infrastructure and compliance with vaccine storage norms were observed at most facilities. However, gaps persisted in stabilizer availability, ice-pack conditioning practices, and vaccine transport logistics, with no CCP having a dedicated vaccine van or trained driver.

Conclusions:

Better compliance in cold chain infrastructure, vaccine logistics, and documentation practices was observed after eVIN implementation. However, gaps in stabilizer availability, ice-pack conditioning, and vaccine transport logistics require targeted programmatic action to sustain improvements in routine immunization services.

INTRODUCTION

Immunization is universally recognized as one of the most cost-effective public health interventions and is the cornerstone of primary healthcare.[1,2] Its success lies in engineering a functional, effective vaccine supply chain, which should manage end-to-end logistics, ensuring effective storage of vaccines, stock management, handling, and rigorous temperature monitoring in the cold chain, thus sustaining an adequate logistics management information system.[3] India’s universal immunization program (UIP) is among the largest in the world, annually serving approximately 2.6 crore newborns and 3 crore pregnant women through around 9,000,000 immunization sessions supported by more than 27,000 cold chain points (CCPs).[4]

However, UIP faces challenges related to infrastructure, erratic vaccine supply, inefficient inventory management, and inconsistent temperature control.[5] To address these bottlenecks, the Government of India, in collaboration with the United Nations Development Programme (UNDP), launched the Electronic Vaccine Intelligence Network (eVIN);[6] an indigenously developed technology system designed to digitize vaccine stocks and monitor cold chain temperatures in real-time through a smartphone application.[7] It integrates human resource training, standardized data protocols, temperature loggers, and cloud-based dashboards to ensure visibility and accountability in vaccine logistics.

Since its phased rollout began in 2015, eVIN has transformed immunization logistics in India.[7] In Madhya Pradesh, eVIN was launched on December 4^th, 2015, and was recognized as one of the best innovations at the National Summit on Good and Replicable Practices in Public Health Care Systems in 2016.[6,8] Evaluation of cold chain infrastructure and vaccine logistics following eVIN implementation may provide useful programmatic evidence for planning and resource allocation. Hence, the present study was undertaken with the objectives to compare the availability and functionality of cold chain infrastructure and to compare vaccine stock management and documentation practices between the pre-eVIN and post-eVIN periods, and to assess cold chain management practices in the post-eVIN period.

METHODOLOGY

The present pre–post observational study was conducted in Indore district, Madhya Pradesh, between January 2020 and December 2021, at all 40 functional CCPs during the post-eVIN period. For comparison, secondary data from 36 CCPs from the pre-eVIN period (2014–2015) was obtained.

The difference in sample size between the pre-eVIN (N = 36) and post-eVIN (N = 40) periods was due to the addition of four CCPs after implementation. A census approach was adopted, including all functional CCPs in Indore district during the study period.

Observation checklists were employed for assessing the various cold chain parameters. The checklist was adapted from the supportive supervision format for Cold Chain and Vaccine Management (Ministry of Health and Family Welfare, Government of India).[9] Since this is a standardized program monitoring tool used by immunization program officials, separate validation was not performed. Face validity was ensured by reviewing the checklist for relevance, clarity, and coverage of key cold chain and vaccine logistics parameters before data collection. As post-eVIN direct observation was conducted by a single observer, interobserver variation was not applicable. The checklist was reviewed for completeness before data collection and used uniformly across all CCPs to ensure consistency of observations.

Pre-eVIN data were obtained from secondary program records (UNDP-eVIN system database and the District Immunization Officer’s Health Management Information System), as standardized observational assessments were not available for the pre-implementation period. Post-eVIN data were collected through direct observation using the checklist. Data were recorded, coded, and compiled using Microsoft Excel. Categorical variables were represented as frequencies and percentages. Since a census approach was adopted, including all functional CCPs in the district during the respective study periods, inferential statistical testing was not performed, as this was a descriptive programmatic assessment rather than population-level estimation. Because pre-eVIN and post-eVIN data were derived from different sources, comparisons were restricted to parameters with comparable definitions and data availability, and all findings were presented using descriptive statistics. Sickness rate was defined as the percentage of cold chain equipment (CCE) that was nonfunctional but repairable at the time of assessment and was calculated using the standard Government of India cold chain monitoring formula.[9]

This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.

Ethical considerations

The study was conducted after approval from the Institutional Ethics Committee.

RESULT

Pre-eVIN data showed sickness rates <2% for all except stabilizers. Post-eVIN, sickness rates were higher, except for cold boxes [Table 1]. With respect to placement, state, and connection to stabilizer of CCE, the post-eVIN period showed better compliance. All CCEs were positioned appropriately, away from direct sunlight, moisture, rain, and walls, with adequate gaps between adjacent equipment. Additionally, 77.5% of CCPs (n = 31) had placed CCEs on designated stands. However, comparison between pre-eVIN and post-eVIN periods could be made based on only one parameter, that is, presence and connection to stabilizers, due to the availability of limited pre-eVIN period data. Table 2 presents a comparison of various parameters pre-eVIN and post-eVIN. Generator was the only type of power back-up available in the pre-eVIN period, while the post-eVIN period saw a shift with most CCPs (n = 16; 55%) adopting solar power back-up. After the advent of solar power back-up, the dependency on generators decreased drastically [Figure 1]. In terms of maintaining appropriate temperature for vaccine and diluent storage, the only parameter available for comparison was the presence of a functional thermometer in each operational unit, due to limited monitoring pre-eVIN [Table 2], indicating better documentation of temperature monitoring post-eVIN. In the post-eVIN period, the temperature of CCEs at each CCP was being recorded twice daily, including Sundays and holidays. Any incidents of power failure were documented in temperature logbooks. Also, cabinet temperature of all functional ice-lined refrigerators (ILRs)/deep freezers (DFs) remained within the recommended range at all CCPs. However, a separate temperature log book for each CCE was available at only 16 (40%) CCPs. With respect to documentation practices [Table 2], it was observed that vaccine stock and distribution registers were not updated regularly in the pre-eVIN period, and data management was predominantly done using Excel or paper registers. In the post-eVIN period, all CCPs followed standardized documentation protocols. All data were entered in registers, as well as eVIN app (web-based). The data capturing post-eVIN is real-time. The advent of eVIN facilitated the monitoring of several additional parameters not captured in the pre-eVIN period [Table 3]. Hence, no comparison was made. It was observed that most CCPs had adequate infrastructure and adherence to good vaccine storage and handling practices, with full compliance reported for parameters like dry storage, technician tools/spares, and ILR storage norms. Handling and usage of ice-packs was generally satisfactory, though gaps existed in correct placement and availability of conditioning space. Challenges remained in vaccine transport, with no CCPs having a trained driver or a functional vaccine van. Vaccines were distributed to session sites through alternate vaccine delivery (AVDs) at all CCPs, for a fee. At 13 CCPs, non-UIP vaccines (COVID-19 vaccines) were stored in ILR. All CCEs were CFC-free, though 6.45% were over ten years old. While most CCPs had no long-term equipment failure, stabilizers were down in eight CCPs, while ILR at four CCPs (these ILRs were additional and vaccines were placed in another functional ILR), and solar power back-up at two CCPs were down for >1 month [Table 4].

Table 1.

Sickness rate of CCE in pre-eVIN and post-eVIN period

CCE	CCE Sickness Rate (pre-eVIN)	CCE Sickness Rate (post-eVIN)
ILR	0.00%	3.79%
DF	0.00%	4.91%
Cold boxes	0.00%	0.00%
Stabilizers	22.7%	12.5%

eVIN=Electronic Vaccine Intelligence Network, CCE=cold chain equipment, ILRs=ice-lined refrigerators, DF=deep freezer

Table 2.

Descriptive comparison of cold chain parameters in pre-eVIN (n=36) and post-eVIN (n=40) period

Parameters		Pre-eVIN CCPs n (%)	Post-eVIN CCPs n (%)
CCE connected to stabilizers (ILR+DF)
All		10 (27.8%)	17 (42.5%)
Some		13 (36.1%)	20 (50.0%)
None		13 (36.1%)	3 (7.5%)
Power availability and power back-up at CCPs
Average hours of power availability (in 24 h) of >20 h in last week	Yes	36 (100%)	40 (100%)
Availability of functional power back-up	Yes	8 (22.2%)	29 (72.5%)
Presence of separate functional thermometer inside every functional equipment
Yes		30 (83.3%)	36 (90.0%)
Documentation practices
Stock register updates until a day before assessment date	Yes	26 (72.2%)	40 (100.0%)
Vaccine distribution register updates until a day before assessment date	Yes	26 (72.2%)	40 (100.0%)
Type of management system for vaccine and logistics management	Excel based	7 (19.4%)	0 (0.0%)
	Paper based	36 (100.0%)	40 (100.0%)
	Web based	0 (0.0%)	40 (100.0%)

CCE=cold chain equipment, CCPs=cold chain points, eVIN=Electronic Vaccine Intelligence Network, ILRs=ice-lined refrigerators, DF=deep freezer

Figure 1.

Type of functional power back-up among CCPs having power back-up in pre-eVIN (8/36 CCPs) and post-eVIN (29/40 CCPs) periods. CCPs = cold chain points, eVIN = Electronic Vaccine Intelligence Network

Table 3.

Assessment of cold chain parameters in post-eVIN period only (n=40)

Parameters		Yes n (%)	No n (%)
Availability of dedicated area for CCPs, syringes/diluents, CCEs, tool kits, spare parts for their repair and maintenance
Dedicated room/space available for cold chain at facility?		39 (97.5%)	1 (2.5%)
Dedicated room/space available for syringes and diluents (dry storage)?		40 (100%)	0 (0%)
Sufficient space available for repair and maintenance of CCEs?		27 (67.5%)	13 (32.5%)
For repair and maintenance, cold chain technician has tool kit		40 (100%)	0 (0%)
For repair and maintenance, cold chain technician has spare parts		40 (100%)	0 (0%)
Handling and usage of ice-packs
Ice-packs correctly placed inside DF for freezing		25 (62.5%)	15 (37.5%)
Ice-packs kept for freezing filled up to mark and capped		33 (82.5%)	7 (17.5%)
Dedicated table/space available for ice-pack conditioning		28 (70.0%)	12 (30.0%)
Clean cloth available for wiping ice-packs after conditioning		35 (87.5%)	5 (12.5%)
Vaccine transport
Driver posted at every CCP		0 (0%)	40 (100%)
Driver trained for CCH module in last 3 years?		0 (0%)	40 (100%)
Is there a functional vaccine van available for vaccine transport?		0 (0%)	40 (100%)
Only UIP vaccines stored in ILR		27 (67.5%)	13 (32.5%)
Vaccine management and handling practices
Vaccine storage in ILR	Within basket	40 (100%)	0 (0%)
	Over two rows of empty ice-packs	0 (0%)	0 (0%)
	Directly on floor of ILR	0 (0%)	0 (0%)
Hep-B/T-series vaccines stored at top in ILR		40 (100%)	0 (0%)
All vaccine vials having proper readable labels		40 (100%)	0 (0%)
All vaccines within expiry dates		40 (100%)	0 (0%)
All vaccines with usable vaccine vial monitor (VVM)		40 (100%)	0 (0%)
Any vaccine in frozen condition		0 (0%)	40 (100%)

CCE=cold chain equipment, CCPs=cold chain points, eVIN=Electronic Vaccine Intelligence Network; UIP=universal immunization program, ILRs=ice-lined refrigerators, DF=deep freezer, VVM =Vaccine vial monitor

Table 4.

Age, functionality, and CFC-free status of cold chain equipment and CCPs in post-eVIN period only

Parameters	Number	Percentage*
CCE >10 years old	18/279	6.45%
CFC-free CCE	279/279	100%
CCPs with no CCE down for >1 month	26/40	65%

CCE=cold chain equipment, CCPs=cold chain points, eVIN=Electronic Vaccine Intelligence Network. *Percentages for CCE >10 years old and CFC-free CCE were calculated using total CCE units as denominator. Percentage for CCPs with no CCE down for >1 month was calculated using total CCPs as denominator

DISCUSSION

The present study assessed changes in cold chain infrastructure and vaccine logistics before and after eVIN implementation and identified key operational gaps requiring programmatic attention.

Functionality of CCEs is important for maintaining vaccine potency. As per national guidelines, CCE sickness rate should be less than 2%, excluding condemned/irreparable units.[9] In the present study, pre-eVIN sickness rates were within limits except for stabilizers. However, post-eVIN sickness rates were higher for ILRs, DFs, and stabilizers. This higher documented sickness rate may be attributed to better monitoring and documentation, and timely feedback from CCPs to repair units after eVIN implementation. The Techno-economic Assessment of eVIN in Madhya Pradesh[6] also noted a high number of nonfunctional CCEs, while reporting lower sickness rates in eVIN versus non-eVIN states. Similarly, the Health Systems Strengthening (HSS) Case Study[10] found nearly all ILRs functional in six districts in 2019, suggesting higher compliance over time. Earlier pre-eVIN assessment had reported higher pre-eVIN sickness rates in Bihar, Kerala, and Gujarat.[11] These findings indicate that digital systems may initially reveal more operational gaps because of better reporting, but this improved visibility is essential for timely corrective action.

In the present study, equipment placement showed good compliance in the post-eVIN period with all CCEs shielded from sunlight, wind, and rain, and placed at the required distance from walls/adjacent equipment as per guidelines.[12] Similar findings have been reported in other studies.[13,14] However, stabilizer availability remained suboptimal. Although CCPs with all CCEs connected to stabilizers increased after eVIN implementation, only 42.5% achieved compliance. Similar gaps were reported by Naik et al.[15] and Chourasiya et al.,[16] while other studies reported higher or complete compliance.[13,17] This shows that though eVIN may improve monitoring, hardware-related gaps still require dedicated procurement, maintenance, and replacement mechanisms.

Reliable power supply and back-up are essential in maintaining the recommended vaccine storage temperature. In the present study, all CCPs reported more than 20 h of power availability in both pre- and post-eVIN periods, meeting recommended standards.[12] Functional power back-up increased after eVIN implementation, with a shift from generators to solar-powered back-up. Similar improvements have been reported in other studies, although inadequate back-up remains a concern in some settings.[14,16,18] The shift toward solar support reflects cold chain infrastructure strengthening beyond the digital component of eVIN.

Temperature monitoring also improved after eVIN implementation, with increased availability of separate functional thermometers in all CCEs. All functional ILRs and DFs maintained cabinet temperature within the recommended range in the present study, as per national guidelines.[12] However, only 40% CCPs had separate temperature logbooks for each CCE, which was an operational gap. Previous studies have also shown variable adherence to temperature monitoring practices across settings.[14,15,16,17,18,19] Although eVIN provides real-time monitoring and alerts, manual logbooks remain important for verification, accountability, and continuity of records when digital access is unavailable.

Documentation practices showed better compliance with recommended standards[12] after eVIN implementation, with updated stock and vaccine distribution registers increasing to 100%. All CCPs also used web-based eVIN documentation reflecting a shift from paper- or Excel-based records to standardized real-time data entry. This finding is consistent with the Techno-economic Assessment,[6] which reported an improvement in stock register completeness after eVIN implementation. Similar improvements have also been reported by Gurnani et al.,[20] Kumar et al.,[21] and the HSS Case Study.[10] This is an important contribution of eVIN, as accurate and timely forecasting, stock redistribution, prevention of stock-outs, and reduction of wastage were strengthened. However, continued use of both paper and digital records may increase the workload of cold chain handlers. Hence, data entry processes may need simplification while maintaining accountability.

Vaccine storage and handling practices in the present study showed high compliance in the post-eVIN period as per recommended guidelines.[12] All CCPs stored vaccines within ILR baskets correctly, maintained readable labels, ensured vaccines were within expiry dates, and had usable vaccine vial monitors. No frozen vaccine was observed. Similar compliance was reported in previous studies, although some assessments documented gaps, such as frozen vials, incorrect placement, or storage of vaccines outside recommended norms.[14,16,18,19,22] The HSS Case Study[10] also showed improvement in vaccine storage practices over time. The Techno-economic Assessment of eVIN[6] highlighted improved management through better adoption of the First-Expiry First-Out method. Thus, the absence of expired, frozen, or unusable vaccines in the present study suggests improved monitoring and documentation for vaccine quality assurance.

Almost one-third of CCPs stored COVID-19 vaccines along with UIP vaccines, possibly due to additional cold chain demand during the pandemic. This highlights the need for adequate space, proper labeling, and clear segregation when additional vaccines are stored with routine immunization vaccines.

Infrastructure availability was satisfactory in the post-eVIN period, with all but one CCP having a dedicated cold chain room and all sites having dry storage space for syringes and diluents, as per guidelines.[12] However, space for repair and maintenance of CCE was inadequate at several facilities. Similar gaps have been reported in previous studies.[13,16,19,23] Thus, while basic cold chain infrastructure improved after eVIN implementation, space constraint for equipment repair and maintenance remains an operational gap.

Ice-pack conditioning practices remained a challenge, with partial adherence to guidelines[9] for correct placement of ice-packs in DFs, filling and capping, availability of dedicated space for conditioning, and use of clean cloth for wiping after conditioning. Similar gaps were reported in earlier studies.[15,16,17,18,19] This indicates that ice-pack handling is a common operational issue, not specifically limited to eVIN implementation. Regular hands-on training, supervision, and adequate conditioning space are needed to improve these practices.

Functional vaccine vans and designated drivers are required for effective vaccine delivery.[9] In the present study, no CCP had a functional vaccine van/posted driver. Instead, vaccines were transported by AVDs on a payment basis. National EVM Assessment[23] and HSS Case Study[10] also reported such reliance due to logistics gaps. Thus, while eVIN can improve stock visibility and storage monitoring, physical distribution still depends on transport infrastructure, trained personnel, and reliable last-mile delivery mechanisms.

Limitations

This study has certain limitations that should be considered, while interpreting the findings. First, the study was conducted in a single district of Madhya Pradesh, which may limit the generalizability of the findings. Second, the pre–post observational study without a control group limits causal attribution of observed changes solely to eVIN implementation. Third, there was asymmetry in data sources, as pre-eVIN data were obtained from secondary program records, whereas post-eVIN data were collected through direct observation using standardized checklists, which may introduce measurement bias and limit direct comparability. Fourth, the difference in the number of CCPs between the two periods due to the addition of new facilities may also affect comparability. Finally, due to differences in data availability and methods of data collection between the two periods, only descriptive comparisons were possible, limiting causal interpretation of the observed changes. However, inclusion of all functional CCPs in the district strengthens the programmatic validity of the findings and provides useful evidence on strengthening vaccine logistics through digital intervention like eVIN.

CONCLUSION

The present study demonstrated better compliance in cold chain infrastructure, vaccine logistics, and documentation practices following eVIN implementation. However, gaps in stabilizer availability, ice-pack conditioning, repair space, and vaccine transport logistics require targeted programmatic action. Priority should be given to ensuring adequate stabilizers for all CCE, proper training on ice-pack conditioning, strengthening repair, and maintenance facilities and improving vaccine transport through dedicated vaccine vans. Thus, eVIN should be supported by continued infrastructure investment, training, and supervision to sustain improvements in routine immunization services.

Key messages

Digital vaccine logistics systems like eVIN may support better cold chain monitoring and documentation practices, thereby strengthening routine immunization.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.