Overall, this study confirmed that a combination of vaccination and ACF measures contributed to favourable results in minimising the case volume and death toll. The greater the vaccination and ACF covered, the greater the volume of cases averted. In addition, the benefit of all combined strategies in terms of total case reduction would be maximised if the epidemic activity, as reflected by R0, was not too intense.
This finding corroborated the ideas of many studies abroad that ACF is a key measure to contain and suppress the epidemic [20]. For example, China reported the use of ACF to identify patients in the epidemic communities [20]. This was performed not only by the state but also by the assistance of community network. Other countries that successfully contained COVID-19 through ACF and close-contact identification included Iceland, Mongolia, Singapore, South Korea, and Vietnam [7, 21, 22]. Singapore maximised detection of suspected patients through a public prevention clinic network and tightly implemented, legally supported home quarantine orders for patients with mild illness [23, 24]. South Korea greatly expanded the scope of testing to detect cases as early as possible with numerous screening sites capable of taking SARS-CoV-2 nucleic acid tests (including public health-care clinics, drive-through centres, and walk-in screening sites) [25, 26].
Traoré and Konané suggested that the contact tracing strategy as well as ACF can reduce R0 to values below unity as intended for disease control, but effective control of the epidemic can be achieved when the effectiveness of contact tracing is high, and R0 is not too large. In the population where R0 is large, the epidemic may not be controlled using ACF strategy alone [27]. Our findings also upheld that idea that such a vaccination policy hugely complements ACF measure. The situation in Samut Sakhon is very complex because the city is extremely urbanised and migrant residents are mostly living in densely populated conditions. These conditions create a remarkable difficulty for ACF and other non-pharmaceutical interventions (NPI), such as physical distancing measure and individual risk modification. At present, ACF is the major intervention in Samut Sakhon with an aim to test all 400,000 workers and isolate those who are positive for 10 days in field hospital or factory dormitory. So far the Government has built up approximately 3,000 field hospital beds. Healthcare providers use individual nasopharyngeal swab for real-time polymerase chain reaction (Rt-PCR) testing. By average it takes at least 48 hours to obtain the swab result. This means ACF alone may not be able to detect and isolate cases as early as expected. Thus, the Thai Government should consider an urgent launch of vaccination policy in Samut Sakhon or in any settings alike once the COVID-19 vaccines are available.
The bottom line is, at the time of writing, the evidence of vaccine effectiveness against COVID-19 transmission is not yet fully understood [28]. Many different endpoints are used in vaccine research to define efficacy depending on the pathogen, consequences of infection, and transmission dynamics. Outcomes of most randomised controlled trials (RCT) are presented as a proportional decline in disease between vaccinated participants and control participants [29]. Other outcomes might include assessing sterilising immunity, severity of resultant clinical disease, and duration of infectivity. Besides, RCTs almost always represent best-case scenarios of vaccine efficacy under idealised conditions; but, in the real world, vaccine efficacy does not always predict vaccine effectiveness and such effectiveness is likely to vary across age groups and people from different walks of life as certain subpopulations in the society may always face greater risk of infection or may be more vulnerable than the others [30]. However, the findings above are of certain value for policy consideration as the vaccine efficacy parameter applied in the model was very modest (only ⁓50%) while recent evidence demonstrated much more favourable outcomes than the 50% figure [14]. For instance, the latest interim analysis from phase 3 clinical trial in Russia by Logynov et al demonstrated that an rAd26 and rAd5 vector-based heterologous prime-boost COVID-19 vaccine (Sputnik V) showed 91·6% efficacy against COVID-19 and was well tolerated in a large cohort [13, 31, 32].
It should be noted that this study contained a few key limitations despite complex model structure and detailed calculation. Firstly, most parameters included in the model derived from the epidemic situation in Samut Sakhon. Therefore, a generalisation of the findings to other areas should be made with caution; though one may use the approach used in this study as an analysis example in any similar settings. Secondly, during the period of epidemic, it is almost always difficult to conduct primary research to obtain empirical evidence as the utmost priority of the field operations was to curb the epidemic. Accordingly, many parameters in the model were obtained from authors’ assumptions. Though we tried to validate the findings against the opinions of experts and local providers, this could not substitute the use of empirical data. Thirdly, the model applied deterministic approach as it is more convenient to communicate with policy makers, compared with stochastic approach and because most parameters in the model lacked information of the distribution characteristic, which is a prerequisite for stochastic analysis. Last but not least, though we demonstrated the benefit of vaccination strategies in this setting, in real practice, the actual implementation needs to consider many more policy angles; for instance, social acceptability (if migrants are supposed to be the vaccination target first before general Thais), cost-effectiveness of the policies, and operational feasibility. Further studies that address these topics are of great value. In addition, a close monitoring of the information in the field is useful, not only for the benefit of disease control, but also for obtaining empirical evidence which will help refine and validate the model.