From lockdown to precise prevention: Adjusting epidemic-related spatial regulations from the perspectives of the 15-minute city and spatiotemporal planning

Abstract

The COVID-19 pandemic challenged emergency management in cities worldwide. Many municipalities adopted restrictive, one-size-fits-all spatial regulations such as lockdowns without fully considering the inhabitants’ daily activities and local economies. The existing epidemic regulations’ unintended detrimental effects on socioeconomic sustainability necessitate a transition from the “lockdown” approach to more precise disease prevention. A spatially and temporally precise approach that balances epidemic prevention with the demands of daily activities and local economies is needed. Thus, the aim of this study was to propose a framework and key procedures for determining precise prevention regulations from the perspectives of the 15-minute city concept and spatiotemporal planning. Alternative regulations of lockdowns were determined by delineating 15-minute neighborhoods, identifying and reconfiguring facility supplies and activity demands in both normal and epidemic conditions, and performing cost-benefit analyses. Highly adaptable, spatially- and temporally-precise regulations can match the needs of different types of facilities. We demonstrated the process for determining precise prevention regulations in the case of the Jiulong 15-minute neighborhood in Beijing. Precise prevention regulations—which meet essential activity demands and are adaptable for different facility types, times, and neighborhoods—have implications for long-term urban planning and emergency management.

1. Introduction

The outbreak of the COVID-19 pandemic has challenged urban epidemic management globally. Urban density and highly mobile citizens have made cities more vulnerable to the infectious virus (Liu et al., 2021). In response, many cities have imposed strict regulations, such as lockdowns, designed to reduce human-to-human contact and slow the spread of the virus (Cheng et al., 2022; Usher et al., 2020). Although lockdowns have proven to be effective in reducing pandemic-related morbidity and mortality, they may also have unintended detrimental impacts on physical and mental health (Corley et al., 2021; Ma et al., 2022) and may exacerbate social segregation and inequalities (Buffel et al., 2021; Li et al., 2022). Thus, most major cities began relaxing COVID restrictions near the start of 2022, when the Omicron variant made the cost of lockdowns exceeded their benefits.

China was an exception to the restriction changes; regional lockdowns continued to be imposed occasionally. These lockdowns not only disturbed everyday life, but also had the potential to cause extensive economic damage (Cheng et al., 2022). As the dilemma between lockdowns and socioeconomic sustainability was recognized by the central government of China, COVID-related regulations became increasingly focused on “precise prevention.” Precise prevention requires the implementation of flexible strategies that are more spatially and temporally precise other than one-size-fits-all lockdowns when infective cases are increasing only in limited areas or cities. Precise prevention also aims to simultaneously prevent the spread of the virus and maintain socioeconomic development (Xinhua, 2022). However, in reality, precise prevention was not perfectly translated into practice. In fact, the number of areas subjected to—and the frequency of—lockdowns began to increase considerably by mid-2022 (Yu, 2022). The tension between lockdowns and socioeconomic sustainability finally forced many Chinese cities to quickly drop most of the COVID-related regulations by the end of 2022, and the result was an explosive increase in infections.

Although the idea of precise prevention is reasonable, several factors in practice hinder it from acting as a transitional stage between strict lockdowns and a complete opening up. As people were spatially restricted within their homes and gated neighborhoods, residents cannot perform their daily activities such as shopping or outdoor leisure in limited space; local economies cannot be sustained as a result of out-of-home activities decrease. In addition, the restrictions were still general, as the same regulations were broadly applied to all cities where outbreaks occur, regardless of their local activity demands and facilities. Moreover, only spatial regulations were being implemented, and less consideration was given to temporal and behavioral dimensions of people's needs and practical regulations. Thus, we sought to explore methods that include spatiotemporal and behavioral factors of various neighborhoods, within cities (see Section 2.2 regarding the 15-minute city concept), to better translate the idea of precise prevention into reality.

The aim of this study was to develop a framework and key procedures for creating precise prevention regulations that can adjust the existing epidemic-related spatial regulations. The study also had a purpose beyond the COVID-related regulations in China: to explore epidemic-related spatial regulations that are more precise and flexible than strict lockdowns, so that urban leaders can better prepare for new epidemics of future infectious viruses and similar public health emergencies. Hence, we examined a key research question: How can epidemic-related spatial regulations support the accomplishment of daily activities as well as local economies while simultaneously preventing infection?

In our approach, we took inspiration from the ‘15-minute city’ concept and spatiotemporal planning because they respond well to the given limitations. The idea of the 15-minute city is that people can live locally if essential amenities are proximate (i.e., 15-minute walking or cycling distances; Legeby, et al., 2022). The 15-minute accessible area is therefore considered an ideal spatial scale for implementing epidemic prevention regulations because residents can more easily maintain their daily activities within this area. The concept also emphasizes that there are no general solutions because the people and geographical contexts vary from one residential area to another. Spatiotemporal planning highlights integrating temporal adjustments and behavioral guidance with spatial planning to formulate more localized and flexible regulations (Pierre, 2020).

This article is organized as follows: Section 2 is a review of the literature on existing spatial regulations during COVID, the 15-minute city concept, and spatiotemporal planning. In Section 3, we introduce the framework and outline the key procedures for determining the specific regulations necessary to achieve precise prevention in various sresidential urban areas. We then apply those to a sample case in Beijing in Section 4 to demonstrate how the framework can be utilized in the real world. Finally, we offer a discussion and our conclusions in Section 5.

2. Literature review

2.1. Spatial regulations during the COVID-19 pandemic

Spatial distancing was the key measure introduced by the World Health Organization (WHO) to combat the spread of SARS-CoV-2, as the infectious virus is transmitted mainly through human-to-human contact (Amirzadeh et al., 2023). Three means of spatial distancing were included in the existing regulations. First, quarantine or stay-at-home requirements restricted residents’ activities to those within their own homes or in their immediate neighborhoods (Lak et al., 2021). Second, restrictions in public spaces were implemented including mandatory “one-meter” distancing, closures of public facilities, prohibited large-scale gatherings, limitations on crowd sizes, and the mandatory use of screens and masks (Cairney, 2021; Kleinman, 2020). The third type of restriction involved complete shutdowns in larger areas to reduce large-scale movements. Residents were required to stop moving between different areas to reduce the spread of virus (Miles et al., 2020).

Overall, these spatial regulations were enacted without much consideration of residents’ activity demands and local socioeconomic sustainability. Moreover, the stay-at-home orders and lockdowns reportedly led to more sedentary behavior, less outdoor activities, and greater social isolation, which further led to higher stress levels, a higher sense of loneliness, and decreased life satisfaction (Ma et al., 2022). Vulnerable groups living in socio-economically deprived neighborhoods were negatively impacted by the ‘double lockdown’ resulting from the interrelated social and spatial inequalities associated with COVID-19 (Li et al., 2022). A large number of economic activities were passively or spontaneously restricted, leading to worldwide economic losses (Cheng et al., 2022).

In addition, these spatial regulations were usually implemented in a general way that neglected variances among different locations and facilities. Given that one-size-fits-all spatial regulation can also put extra pressure on socio-economically deprived neighborhoods (Buffel et al., 2021), pandemic regulations should be more tailored to different situations to avoid detrimental effects. Specifically, temporal adjustments and behavioral guidance can be integrated with spatial measures to generate more precise and flexible regulations than traditional lockdowns.

2.2. The ‘15-minute city’ in epidemic conditions

The concept of the ‘15-minute city’ requires that basic urban amenities should be located within 15 minutes walking or bicycle distances (Pozoukidou & Chatziyiannaki, 2021). Six essential functions, namely, living, working, commerce, healthcare, education, and entertainment, should be fulfilled within a 15-minute distance; hence proximity—rather than accessibility—is highlighted as one of the fundamental principles of the 15-minute city concept (Moreno et al., 2021). In China, a similar concept, the ‘community life circle,’ describes an aggregated activity space designated for essential daily activities within a proximate residential area. Community-life-circle planning calls for a configuration of neighborhood facilities that optimizes activity space, for example, by ensuring that it is within a reasonable (15-minute) range for the residents in the neighborhood.

Both the 15-minute city and community life circle concepts have received worldwide attention in urban planning research and practice (Chai & Li, 2019; Pozoukidou & Chatziyiannaki, 2021). The ideas have attracted even more interest during the COVID pandemic. The epidemic-related spatial regulations required residents to perform everyday activities at home or near home (Legeby et al., 2022), urging urban planners to reconsider redesign of contemporary neighborhoods to improve their resilience and sustainability in the post-pandemic era (Pierre, 2020). Proximity to essential facilities in neighborhoods was highlighted in Greek cities seeking to promote health outcomes and wellbeing (Mouratidis & Yiannakou, 2021). Similarly, Guzman et al. (2021) emphasized the role of 15-minute city planning in redressing social and spatial inequalities. In Milan, 2020 Adaptation Strategy was applied in a post-pandemic urban planning project to strategically reorganize the city's spatiotemporal resources in the city (Pinto & Akhavan, 2022).

The concept of the 15-minute city provides a model of the optimal spatial unit for effective and efficient epidemic regulation. As adequate and accessible facilities are provided within each 15-minute neighborhood, residents can meet their daily demands while staying within a relatively small geographical area. The goal of reducing virus transmission can be achieved by providing a proximate activity space rather than implementing strict stay-at-home orders or massive lockdowns. This approach to epidemic emergency management also supports sustainable local economies and low-carbon lifestyles (Pinto & Akhavan, 2022). In addition, the idea behind the 15-minute city emphasizes awareness. Therefore, taking 15-minute neighborhood as a basic spatial unit for epidemic regulations and for estimating the local supplies and demands in each neighborhood fit the idea of precise prevention.

2.3. Spatiotemporal planning in epidemic conditions

The 15-minute city idea encompasses the basic principle of precise prevention; however, decisions on the actual epidemic regulations with detailed measures for residents and facilities still rely on spatiotemporal planning strategies. The aim of spatiotemporal planning is to improve the organization of spatiotemporal resources and behavioral needs from the dimensions of supplies and demands (Mey & Ter Heide, 1997), including three fundamental strategies. On the supply side, spatiotemporal planning attempts to (re)organize urban resources to better satisfy behavioral needs (Hägerstrand, 1970). First, the spatial strategy guides the improvement of provisions and greater accessibility to local facilities according to the local demand (Kamiya, 1999; Li et al., 2021). Second, temporal strategy coordinates facilities’ operating hours to match the times when individuals are available to use them (Marsal-Llacuna & Fabregat-Gesa, 2016; Niedzielski et al., 2020). On the demand side, the third strategy—the behavioral strategy—encourages people to change their behaviors in space and time (i.e., in the spatiotemporal context) to make better use of existing resources (dos Reis et al., 2022; Jariyasunant et al., 2015). Guidance on personal trip planning and behavioral intervention policies help citizens to re-arrange their daily lives in healthier and more environmentally friendly ways (Orban et al., 2014; Palm & Ellegård, 2011; Tseng et al., 2013).

The integration of spatiotemporal planning in epidemic regulations could provide more flexible measures than those conventional ones. Spatiotemporal dynamics are important to a neighborhood's resilience capacity (Kontokosta & Malik, 2018), and negative effects of complete shutdowns could be partly avoided if facilities were allowed to open as long as necessary social distancing were maintained (Mitra et al., 2020). Regulating staggered operating hours for different facilities as a temporal strategy can reduce overlaps in time windows where people encounter each other and, thus, reduce the risks of infection (Pozoukidou & Chatziyiannaki, 2021).

However, to our knowledge, few studies have examined the systematic integration of the 15-minute city concept and spatiotemporal planning to improve epidemic regulations. Specifically, although some measures comprised both spatial and temporal dimensions, they overlooked variations in facilities and time periods (Jiang et al., 2020). For example, in the early pandemic stage in Italy, residents were allowed to move within a 200-meter range of their homes, and commercial facilities were open from 6:00 am to 6:00 pm (Mattei & Delpino, 2021). Although facilities were accessible with certain distances and certain time periods, they were still inaccessible for residents living in low-density areas and those who work in the daytime and can only shop after 6:00 pm. Additionally, behavioral strategy has received little attention. By providing information about when and where residents could go, residents can perform daily activities while reducing infective risks. How these strategies can be proposed is discussed in detail in Section 3.

3. Framework and key procedures for determining precise prevention regulations

The primary purpose of precise prevention is, through careful analysis and reconfiguration of local supplies and demands, to determine the epidemic prevention regulations that not only prevent infection but also support daily activities and local economies. A framework of precise prevention is established (Fig. 1 ). Current epidemic-related spatial regulations have the problems of limited spatial scale, “one-size-fits-all,” and only in the spatial dimension. Inspired by the 15-minute city concept and spatiotemporal planning, we propose the decision-making procedures based on two principles: (1) during epidemics, free movements are encouraged but limited to areas within the 15-minute neighborhood, and (2) a combination of one or more strategies are used to provide and (re)allocate spatiotemporal resources within the 15-minute neighborhoods. Four key procedures for determining the precise prevention regulations are summarized below; detailed descriptions are provided in separate subsections.

• Step 1. Delineate and establish 15-minute neighborhoods as the basic spatial unit for the subsequent steps.

• Step 2. Acquire and analyze data on individuals’ behaviors and local facilities to identify the spatiotemporal demands and supplies within the 15-minute neighborhoods in normal conditions. Consider spatially and temporally precise regulations according to various facilities and different 15-minute neighborhoods. Also analyze the demands and supplies in different time periods of 24h in weekdays and weekends.

• Step 3. Generate regulations by combining one or more of the spatiotemporal planning strategies. Reconfigure supplies and demands across different regulation scenarios in epidemic conditions. Evaluate further the regulations that are considered feasible, i.e., only those that satisfy both the activity demand and epidemic-prevention requirements.

• Step 4. Perform cost-benefit analysis (CBA) to determine which of the feasible regulations is optimal, i.e., offering the greatest benefits at relatively lower costs.

Fig. 1.

The framework and key procedures for determining precise prevention regulations.

When this process is applied, planners must recognize that the local facilities in some neighborhoods may not be sufficient to meet local demands in epidemic conditions; thus, precise prevention may not be feasible. In these circumstances—wherein 15-minute neighborhoods lack some spatial and temporal resources—urban planning that includes physical adjustments is required to ensure local facilities and resources in15-minute neighborhoods will be sufficient to meet local needs when future epidemics occur.

3.1. Step 1: Delineate and establish 15-minute neighborhoods

As an initial step, the 15-minute neighborhood is delineated as the spatial analysis unit (Fig. 2 ). Exiting context-based crystal growth (CCG) method provided by Li et al. (2021) is improved by setting every residential building as growing seed and making hierarchical clustering of residential building-based 15-min walking accessible area. Then, the 15-minute neighborhoods are determined by hierarchical clustering of each residential-building-based 15-minute-walking accessible range. The clustering method ensures that facilities are equally accessible to all of the residents within a neighborhood. Although this tenet does not guarantee that every resident can access all facilities within exactly 15 minutes, the farthest distance should be walkable within approximately 15 minutes.

Fig. 2.

Delineation of 15-minute neighborhoods.

3.2. Step 2: Identify the demands and supplies in normal conditions

3.2.1. Local demands in normal conditions

In space-time behavior research, behavioral demand is usually estimated according to the total amount of time spent on daily activities (Ellegård, 2018). We improved the estimate by (1) considering the variations of population groups and (2) dividing a single day into several periods to address the uneven distribution of activity demands over time. The overall demand in a 15-minute neighborhood of a certain type of activity i in time period t, denoted as $D_{i.t}$, is calculated by Equation (1). The selection of activity type is consistent with the essential functions in the 15-minute city literature, which are living, working, commerce, healthcare, education, and entertainment; however, specific local contexts should be considered; for example, for residents who do not work in a certain 15-minute neighborhood in normal conditions, work activity should not be considered ‘essential.’

$$D_{i.t}=\sum _{p}deman{d}_{p,i}*pr{o}_t*po{p}_p$$ (1)

where $deman{d}_{p,i}$ is the average time group p spent on activity i on a day; $pr{o}_t$ is the demand ratio in time period t; and $po{p}_p$ is the population of group p in the 15-minute neighborhood.

3.2.2. Local supplies in normal conditions

Theoretically, the spatiotemporal supply of a certain type of urban resource is equal to the sum of the spatiotemporal supply of all related facilities. Here, the spatiotemporal supply of each facility can be estimated by the product of its opening hours and capacity. However, given that the actual capacity of each facility is difficult to ascertain, we use the average facility capacity instead. Additionally, facility types correspond to activity types. For example, all facilities within the 15-minute neighborhood that can fulfill the ‘leisure activity’ role are considered ‘leisure facilities.’ Therefore, cases wherein types overlap within one facility may include several calculations. For example, for a shopping mall, each store within the facility is calculated. Moreover, facility supply in spatiotemporal terms is divided into the same number of time periods as that of spatiotemporal demand. The total supply of a certain type of facility i in a certain time period t, denoted as, $S_{i.t}$, can be calculated in Equation (2).

$$S_{i.t}=\sum _{j}c{\left(N\right)}_{i,t}*duratio{n}_{j,i,t}$$ (2)

where $c{\left(N\right)}_{i,t}$ is the average facility capacity of facility type i in the time period t; $duratio{n}_{j,i,t}$ represents the operating hours of each facility j of type i in time period t.

3.2.3. Average facility capacity in normal conditions

Based on market equilibrium, in normal conditions, it is reasonable to assume that the demand of a certain activity type i is equal to the supply of the corresponding facility type i within each 15-minute neighborhood. Therefore, the average facility capacity, namely, $c{\left(N\right)}_{i,t}$ , is estimated by dividing the supply by the demand (Equation (3)). Considering that facility capacity does not increase or decrease in different time periods, the maximum facility capacity of each type of activity or facility i, denoted as $C{\left(N\right)}_i$ , is the average facility capacity in normal conditions (Equation (4)). It is an important indicator: by comparing facility capacity in normal with epidemic conditions, we can determine whether a regulation is feasible. A detailed description is provided in Section 3.3.

$$c{\left(N\right)}_{i,t}=D_{i,t}/S_{i.t}$$ (3)

$$C{\left(N\right)}_i=max\left(c{\left(N\right)}_{i,t}\right)$$ (4)

3.3. Step 3: Reconfigure demands and supplies in epidemic conditions

3.3.1. New local demands in epidemic conditions

By combining spatial, temporal, and behavioral strategies, regulations of precise prevention in a certain 15-minute neighborhood can be generated. However, these regulations may further change the local demands and supplies. Thus, to determine whether one regulation is feasible, namely, whether behavioral demands could be satisfied while preventing the epidemic, the new demands and supplies must be simulated under different regulations. Therefore, for each regulation, there will be a corresponding demand and supply to determine its feasibility.

On the demand side, residents may spend less time on out-of-home activities as a result of increasing anxiety about infection, leading to less total activity demands. Also, the behavioral guidance may prompt them to rearrange their daily schedules to avoid crowds. The total demand of the activity i in the time period t in epidemic conditions is therefore calculated by Equation (5):

$$D_{i,t}^{\prime }=\sum _{p}sfp*deman{d}_{p,i}^{\prime }*pr{o}_t^{\prime }*po{p}_p$$ (5)

where sfp represents citizens’ safety perceptions of the risk to perform out-of-home activities, which ranges from 0 to 1. If individuals have higher safety perception (when sfp is closer to 1), their activity demands will be reduced less voluntarily; otherwise, the total demand will drop more. The $deman{d}_{p,i}^{\prime }$ and $pr{o}_t^{\prime }$ represent the demand of activity i for the population group p and the new proportion of the demand in the time period t in epidemic conditions.

3.3.2. New local supplies in epidemic conditions

The supply of urban resources also changes according to the epidemic regulations. Spatial and temporal measures including regulations of openness, operating hours, and maximum crowd size of facilities may influence the supply. Equation (6) represents the new supply of facility type i in the time period t,

$$S_{i,t}^{\prime }=\sum _{j}c{\left(N\right)}_{i,t}*ope{n}_{j,i}*crow{d}_{j,i}*duratio{n}_{j,i,t}^{\prime }$$ (6)

where$c{\left(N\right)}_{i,t}$ is the average facility capacity of facility type i; $ope{n}_{j,i}$ indicates whether type i of facility j is allowed to open according to regulations; $crow{d}_{j,i}$ represents restrictions on the crowd-size adjustments of type i for facility j, ranging from 0 to 1, and $duratio{n}_{j,i,t}^{\prime }$ denotes the new operating hours of type i for facility j in time period t according to the regulations.

3.3.3. Required facility capacity in epidemic conditions for feasible regulations

Due to changes in local demands and supplies during the epidemic, the market equilibrium in normal conditions may break down. Therefore, a required average facility capacity in epidemic conditions can be obtained by dividing the new demand by the new supply (Equation (7)).

$$c{\left(P\right)}_{i,t}=D_{i,t}^{\prime }/S_{i,t}^{\prime }$$ (7)

In reality, the required facility capacity in epidemic conditions should not exceed the maximum capacity in normal conditions; otherwise, the regulations could not be implemented. We use $k_{i,t}$ to compare between $c{\left(P\right)}_{i,t}$ and $C{\left(N\right)}_i$ and determine under which regulations the new supply can satisfy the new demand under epidemic situations.

$$k_{i,t}=\{\begin{array}{c}c{\left(P\right)}_{i,t}/C{\left(N\right)}_i,if{D}_{i,t}^{\prime }>0and{S}_{i,t}^{\prime }>0\\ 0,if{D}_{i,t}^{\prime }=0\\ -1,if{S}_{i,t}^{\prime }=0and{D}_{i.t}>0\end{array}$$ (8)

When $D_{i,t}^{\prime }>0$and $S_{i,t}^{\prime }>0$, the value of $k_{i,t}$ is greater than 0. If $0<k_{i,t}\le 1$, the supply of type i of facilities in the time period t can satisfy the demand of activity type i in the same time period t. In that case, the regulation being considered can be regarded as a feasible regulation. If $k_{i,t}>1$, the supply cannot satisfy the demand; this condition may be the result of inappropriate regulation or inadequate existing facilities. Special explanations for $k_{i,t}$ are suggested for two conditions: when the total demand and/or the total supply drop to 0.

3.4. Cost-benefit analysis (CBA) for the optimal precise prevention regulations

The costs and benefits of feasible regulations generated by the above process are compared to determine the optimal regulation. Generally speaking, spatial and temporal strategy—such as closing high-risk facilities, keeping social distance, and adjusting opening hours—are easier to implement than behavioral strategy, as behavioral strategy requires more organization and communication with residents. However, sometimes behavioral strategy would be more efficient. Therefore, in practice, stakeholders should apply one of the following approaches to conduct CBA according to the context and the available data.

The first and most commonly used approach is a financial approach (Schofield, 2018), in which the most efficient solution is identified by translating predicted costs (public expenditures or economic setbacks) and benefits (increased health benefits and reduced infection risks) into money (Cairney, 2021; Robinson et al., 2021). When evaluating monetary value is difficult, investigations into willingness-to-pay or required compensation can be used as alternative approaches. By asking people the maximum/minimum price they are willing to pay, we can determine whether and to what extent people are willing to accept these restrictions (Ryen & Svensson, 2015). Regulations that are strongly rejected by the public should be considered ineligible for implementation. Finally, if financial evaluation and survey evaluation cannot be applied, one could list the important intangible effects and provide qualitative information about the relative significance of different regulations; however, this method is reserved unless needed as the last solution (Schofield, 2018). In our case, describing the relative significance of different regulations based on their prevention effects, administrative costs, or public acceptability can also be helpful for determining optimal precise prevention regulations.

4. A demonstration of the decision process of precise prevention regulations

4.1. Case area and data

In this section, we describe the case study that demonstrates the framework and key procedures for determining precise prevention regulations. We chose the Shuangjing sub-district in Beijing, China as the case area. Because of the variety of residential and commercial functions therein, Shuangjing is representative of 15-minute neighborhoods with adequate and accessible facilities and a typical area to implement precise prevention regulations. Using the extended CCG method, the Shuangjing sub-district was divided into five 15-minute neighborhoods (Fig. 3 ).

Fig. 3.

The location of the Shuangjing sub-district and its 15-minute neighborhoods.

Although precise prevention regulations are determined by different neighborhoods, the procedures are the same. Therefore, we chose one case, Jiulong, out of the five 15-minute neighborhoods, as it was the best option for demonstrating the decision process in detail.

Activity demand data were obtained from an activity-travel survey conducted in the Shuangjing sub-district from June to August 2020. Residents were recruited with the help of local residential communities. All family members were encouraged to participate in our survey. Respondents were asked to complete an online activity-travel diary and recall their activities on a typical weekday and weekend before the pandemic (i.e., in normal conditions). In total, the diaries of 80 participants from 48 families were collected, producing 1,739 valid activity records. Additionally, mobile phone data collected by SMART STEPS (http://www.smartsteps.com/) were used to determine the population of each group in the Jiulong 15-minute neighborhood. To measure the supply of urban resources, the geographic locations and operating hours of facilities were collected through a field investigation and from the API of Baidu Map (https://lbsyun.baidu.com/).

4.2. Identification of local demands and supplies in normal conditions

Based on the research about 15-minute neighborhoods and the survey data of Jiulong 15-minute neighborhood, we focused on three essential out-of-home activities: dining, shopping, and leisure activities. We selected these activities for two reasons: (1) residents in the case area spent much time in these activities (Table A.1), and (2) these activities are important for the residents’ physical and mental health. Corresponding facilities in the neighborhood were then selected. Dining activity corresponded to catering facilities, including fast-food restaurants, beverage shops, and dessert shops; shopping activity corresponded to shopping facilities, including shopping centers, supermarkets, and grocery stores; leisure activity corresponded to leisure facilities, including parks, cinemas, and gyms.

Activity demands in normal conditions were estimated using Equation (1). Two age groups were determined to represent the varied demand of the area's different age demographics, including (1) people aged 65 and younger and (2) people aged above 65. The age structure of mobile phone data was consistent with our survey, which indicated that the activity demand we identified from diaries was representative of the whole population (Table A.1).

The activity demand varied in terms of activity types and time periods, which indicated that precise regulations on different facilities were necessary. We divided a day into 10 periods based on the routine of everyday life: t₁ = 0:00–6:00, t₂ = 6:00–8:00, ..., t₄ = 10:00–12:00, t₅ = 12:00–14:00,..., and t₁₀ = 22:00 –24:00. The demand for dining, shopping, and leisure activity in each time period, on both weekdays and weekends, are shown in Fig. 4 . Shorter-lasting and higher activity peaks occurred on weekdays compared to weekends, wherein peaks were smaller but longer-lasting. Dining activity was more rhythmic, having two peaks, while shopping and leisure activities were more flexible in time.

Fig. 4.

Total activity demands in different time periods on weekdays and weekends.

Corresponding to activity demands, the supplies of three types of facility were collected from field investigation and Baidu Map. In total, we obtained the spatial locations and operating hours of 484 catering, 724 shopping, and 105 leisure facilities. The average capacity of each type of facilities on weekdays and weekends in normal conditions was calculated using Equation (2) and (3) and shown in Fig. 5 . Generally speaking, leisure facilities ranked the highest among the three facility types, as leisure facilities usually have larger space. Shopping facilities accommodated the largest number of visitors in the morning (from approximately 6:00 to 8:00), indicating they also have relatively large area. The average capacity of catering facilities was lower because most of them operated within small spaces. Then, the maximum average facility capacity was estimated for each type of facility using Equations (4). The maximum values for catering, shopping, and leisure facilities were 63.3, 108.0, and 295.4 persons, respectively. Again, the diversity of facility capacity necessitated precise regulations in different periods of time and on different facilities.

Fig. 5.

Average capacity of different facility types in different time periods.

4.3. Reconfiguration of demands and supplies in epidemic conditions

In epidemic conditions, spatial, temporal, and behavioral strategy can be combined to generate regulations that further impact the demands and supplies. In practice, there are many ways to apply such strategies. For example, in terms of spatial strategy, policymakers can close facilities or restrict crowd flows in each facility. Synchronization or desynchronization of operating hours or working schedules could be useful in adjusting temporal resources. For behavioral strategy, apart from releasing information for staggered use, governments can also encourage substitutive out-of-home activities among household members (e.g., young parents might go out to shop and buy goods for the whole family to reduce the infection risks for children and older adults).

In the case we examined, we focused on strategies that were practical considering the local contexts (Beijing, China). According to the Beijing municipal government, the facilities inside shopping malls were not allowed to open during the pandemic; other facilities were required to limit the number of users (customers) to 75% of their normal maximum capacity (Beijing Municipality, 2020, 2022). These basic restrictions were considered to accommodate the general spatial strategy, which applied to all possible regulations in the case area. Additionally, the temporal strategy involved adjustments to facilities’ operation hours. A behavioral strategy was also applied to encourage staggered use of facilities, which would be managed using real-time information about crowd size, and guidance about where and when people were permitted to go was provided to reduce infection risks.

By combining different strategies, we examined four regulation scenarios: spatial strategy, spatial + temporal strategies, spatial + behavioral strategies, and spatial + temporal + behavioral strategies. New demands and supplies were simulated under each regulation scenario (Table B.1).

Two assumptions were made in the calculation of the new demands and supplies. First, the total demands in epidemic conditions (i.e., under each regulation scenario) was assumed to be the same as the ones in normal conditions, though the demands would differ between various time periods. This ‘normal conditions’ premise was used because the basic idea behind precise prevention is to maintain daily activities and economics in the local area in epidemic conditions.

Second, the indicator of sfp was set to 1 in this case with the assumption that people remain willing to perform all their out-of-home activities within a proximate area and meet their neighbors.

Hence, by examining the four regulation scenarios, we obtained the required capacity for various facilities in different time periods. We calculated the values of $k_{i,t}$ by comparing the maximum capability and the required capacity under different regulations (Fig. 6 ). In the figure,$k_{i,t}=1$ in the red-dash line indicates a threshold. For $0<k_{i,t}\le 1$, new supply in epidemic conditions could satisfy the behavioral demand. Correspondingly, the regulations were the feasible regulations of precise prevention (Equation (8)). If none of the regulations proposed were feasible, that result suggested a shortage of local supply in pandemic conditions, indicating the necessity of supplementing spatiotemporal resources in urban planning (e.g., providing more catering facilities that are available on weekends).

Fig. 6.

The values of $k_{i,t}$ under different scenarios; $k_{i,t}$= 1 in the red-dash line indicates a threshold.

4.4. Cost-benefit analysis and decisions on precise prevention regulations

In this case, we conducted a qualitative CBA to determine which precise prevention regulation is optimal for each facility category on weekdays and weekends (Table B.2). The regulations with the behavioral strategy tended to be more difficult to implement because of the need for (1) an established system with real-time calculations of crowd size based on mobile phone data and (2) a platform to release the information and behavioral guidance.

The regulation that offered relatively more benefits and lower costs was considered the optimal precise prevention regulation. For example, in Fig. 6 Panel e, for leisure facilities on weekdays, the distribution and the value of $k_{i,t}$ indicated that both the spatial strategy and the spatial + behavioral strategies were able to satisfy demand while simultaneously preventing viral spread because the $k_{i,t}$ was greater than 0 but less than 1 for all time periods. The priority of the regulations further indicated that spatial strategy was the optimal choice for leisure facilities in the Jiulong 15-minute neighborhood on weekdays during the pandemic. Similarly, we were also able to determine the following precise prevention regulations for other facilities in the Jiulong 15-minute neighborhood on weekdays and weekends:

• •For catering facilities on weekdays – spatial strategy
• •For catering facilities on weekends – all regulation scenarios failed to meet the demand, which calls for a need to increase spatial or temporal resources
• •For shopping facilities on weekdays – spatial + temporal strategies
• •For shopping facilities on weekends – spatial + temporal strategies
• •For leisure facilities on weekdays – spatial + behavioral strategies
• •For leisure facilities on weekends – spatial + temporal + behavioral strategies

5. Discussion and conclusion

This study explored a framework and key procedures for determining precise prevention regulations in epidemic conditions with the goal of epidemic prevention while maintaining daily activities and sustaining local economies. Precise prevention regulations can further act as more precise measures than existing epidemic spatial restrictions, such as lockdowns. Inspired by the 15-minute city concept and spatiotemporal planning methods, precise prevention regulations were determined for different types of facilities in each 15-minute neighborhood. The decision process includes delineating 15-minute neighborhoods as the basic spatial units, identifying out-of-home activity demands and local supplies in normal conditions, reconfiguring the demands and supplies under epidemic regulations, and performing CBA analysis of feasible regulations. We presented a detailed case of a 15-minute neighborhood in Beijing, and the results affirmed the necessity of applying different regulations for different facilities in a specific 15-minute neighborhood.

The precise prevention presented in this study contributes to existing studies and policies in several ways. First, 15-minute walking/cycling accessible areas comprise an ideal spatial unit for epidemic spatial regulations that are effective for preventing viral spread while supporting activity demands and local economies. Second, the regulations are precisely configured for specific times and spaces and are highly adaptable to different types of facilities. Third, temporal and behavioral strategies are addressed as important supplements to existing spatial measures to propose more flexible regulations in epidemic conditions. To our knowledge, this is the first study to promote a framework and key procedures of precise prevention inspired by the 15-minute city approach and spatiotemporal planning, two concepts that have received substantial attention in the pandemic and post-pandemic eras. The results of this study highlight that there are no one-size-fits-all regulations for all types of facilities over broad geographical areas (Manski, 2020). The proposed framework can provide enlightenment for improving COVID-19 epidemic control measures, managing future epidemics, and regulating populations in the face of other hazardous situations.

In epidemic conditions, precise prevention regulations can provide a means of sustaining normal activity demands and ensuring adequate supplies within 15-minute neighborhoods. However, the demonstration case suggests the possibility that supply may not always be able to satisfy demand for some types of facilities, during some time periods and in some neighborhoods. In such cases, when the local demand cannot be fulfilled under the given epidemic regulations, further physical spatial planning improvements are needed. Nonetheless, the time required to improve spatial resources is usually much longer than the duration of an urgent epidemic situation. Therefore, policymakers should also consider temporal and behavioral strategies for coping with spatial supply shortages based on spatiotemporal planning. For example, behavioral guidance can help residents reduce their out-of-home activity demand; certain essential facilities, such as markets and pharmacies, can extend their operating hours and increase local supply.

The study also provides two broader implications for urban planning and management. First, a lack of spatiotemporal diversity among existing facilities can lead to enormous insufficiency, especially during an emergency such as a pandemic. As shopping malls that integrate dining, leisure, and other activities with shopping have become the most common urban commercial spaces (Ozuduru et al., 2014), shutting down these commercial complexes in epidemic conditions would cause significant supply shortages. To better prepare for epidemic emergencies, urban planning should emphasize variation in the geographic locations of facilities and their operating hours. Second, long-term improvements to proximal urban resources within 15-minute neighborhoods are advocated. Promoting sustainable lifestyles when daily activities in the long term is as important as responding to an epidemic crisis when activity is restricted to a limited area (Moreno et al., 2021). Increased local accessibility also helps alleviate spatial inequalities among residential areas and promotes social equity (Guzman et al., 2021).

Some limitations need to be addressed despite the strong policy implications. First, due to a lack of abundant data, we simulated the relatively simple regulation scenarios for demonstration purposes which may differ from reality. However, the aim of this study was to propose a precise prevention framework and key procedures. While we managed to accomplish that aim, further research is required to apply the methods to explore more specific and effective regulations in actual practices. Meanwhile, given the focus on a neighborhood area, working activities, commodity supply chains, and urban transportation were not thoroughly considered in this research. Specific and reliable logistics are important to successfully manage a 15-minute neighborhood because materials, which should be delivered on time, come from areas outside of the 15-minute neighborhoods. This issue becomes even more relevant in epidemic conditions when people perform nearly all of their daily activities within the local area. Therefore, an interesting question is raised as to how supply chains and related logistics should be organized to support the efficiency of the 15-minute neighborhoods, which is recommended as a critical topic for future research involving the15-minute city concept.

Declaration of Competing Interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Appendix A. Dataset

Table A.1.

Information of samples and time allocation of essential out-of-home activities.

	Samples of activity-travel survey		Samples of mobile phone data			Duration of out-of-home activities on weekday (min)			Duration of out-of-home activities on weekend (min)
	N	%	Number of grids (250m x 250m)†	Aver. N	Aver. %	Dining	Shopping	Leisure	Dining	Shopping	Leisure
≤65	72	90	25	17262	92	149.77	65.46	136.80	121.10	129.29	178.22
>65	8	10		1501	8	82.23	42.60	97.32	113.10	108.00	127.50

^†The Jiulong 15-minute neighborhood is covered with twenty-five 250 m x 250 m grids of mobile phone data. The average number of people and percentage of all grids are provided to compare activity-travel survey data and mobile phone data. Generally speaking, the age structure of the activity-travel survey is so close to that of mobile phone data that our samples are sufficiently representative of all residents.

Appendix B. Demand, supply and CBA of regulations

Table B.1.

Changes in demand and supply under different regulations.

Regulation scenario	Dining※	Shopping	Leisure
Spatial strategy	Supply: No further control on crowd size after reducing it to 75%. Demand: Citizens’ behavioral demand remains the same as in normal conditions
Spatial + temporal strategies	Supply: Facilities are allowed to be open only during three time periods: 8:00–10:00 am, 12:00–2:00 pm, 6:00–8:00 pm; crowd size is reduced to 75%. Demand†: No further control	Supply: Facilities are allowed to be open only from 10:00 am–8:00 pm, plus crowd size is reduced to 75%. Demand††: No further control
Spatial + behavioral strategies	Not applicablebecause dining demand cannot be evenly distributed throughout the days.	Supply: No further control on crowd size after reducing it to 75%. Demand: Under behavioral guidance, the total demand from 10:00 am–8:00 pm is evenly distributed during this period; demand in other time periods remains the same as in normal conditions.
Spatial + temporal + behavioral strategies	Not applicablebecause dining demand cannot be evenly distributed throughout the days.	Supply: Facilities are allowed to be open only from 10:00 am–8:00 pm. Demand: Under behavioral guidance, the demand throughout the day is evenly distributed between 10:00 am– 8:00 pm.

^※Due to the temporal fixity of dining activity, asking residents to observe staggered eating hours is unreasonable. Therefore, the restriction on operating hours for catering facilities must differ from the restrictions on shopping and leisure facilities. Due to the same reason, regulations containing the behavioral strategy are not applicable on dining activity.

^†In order to maintain the total demand, the demand outside the opening hours in normal conditions was assumed to be replaced in the closest opening hours.

^††The demand outside the opening hours in normal conditions was evenly distributed between 10:00 am and 8:00 pm when the demand under this regulation scenario was simulated.

Table B.2.

Cost-benefit analysis and prioritization of four regulations.

Regulation scenarios	Benefits	Costs	Priority
Spatial regulation	•Reduced contact in space	•Supervision of closure of interior facilities and crowd size of exterior facilities	3
Spatial +temporal regulation	•Reduced contact in space •Reduced contact in time	•Supervision of closure of interior facilities and crowd size of exterior facilities •Formulation of time regulations and supervision of operating hours of exterior facilities	1
Spatial +behavioral regulation	•Reduced contact in space •Reduced risk of infection through staggered use of facilities	•Supervision of closure of interior facilities and crowd size of exterior facilities •Establishment of a system with real-time calculation of crowd size and a platform releasing the information and behavioral guidance	4
Spatial + temporal + behavioral regulation	•Reduced contact in space •Reduced contact in time •Reduced risk of infection through staggered use of facilities	•Supervision of closure of interior facilities and crowd size of exterior facilities •Formulation of time regulations and supervision of operating hours of exterior facilities •Establishment of a system with real-time calculation of crowd size and a platform releasing the information and behavioral guidance	2

Data availability

• Data will be made available on request.