In this section, we continue to build the alternative strategy (social pendulum) based on socio-geometric constructs developed in the previous sections. The set of constructs are then designated as the model, which helps us to develop scenarios of the situation under the ‘old normal’ (without the strategy of containment) and the ‘new normal’ (under the strategy of containment) in the context of a pandemic (COVID-19).
Why the Containment Strategy Failed on Efficacy
We explore four policy scenarios (what-if) that might have impacted on the efficacy of the containment strategy; epidemiological characteristics of the COVID-19, quality of housing, migratory behavior of residents, and social safety nets.
The epidemiological characteristics (transmission and infectivity profile) of COVID-19 remain uncertain. Indeed, SARS-CoV-2 has been found to exhibit high transmissibility potential estimated to be between 2.2 and 3.11 significantly larger than 1. When R0 is greater than 1, it means that there is a possibility of cases growing exponentially leading to an epidemic or even a pandemic (Zhao et al. 2020; Read et al. 2020). COVID-19 generally carries the course of mild to no clinical symptoms during the incubation period that may last up to 3 weeks, making these people capable of continuing with their daily routines and spreading the infection unperturbed to the unsuspecting population. Other studies have reported that oro-fecal transmission may also be possible (Danchin et al. 2020). Therefore, as projected by our model, suppressive policies such as staying at home and banning non-essential travels can significantly reduce the reproduction rate of the virus. However, although these measures can play crucial role in controlling transmission, the predisposition of slum residents to risk factors such as lack of sanitary facilities and overcrowding is likely to increase their vulnerability to an outbreak or exponential transmissions. This implies that for any PHI to have long-term impact on the population, the strategy must be implemented in tandem with other socio-economic measures. In efforts to address the limitations of mitigation and suppression measures, various predictive mathematical models for epidemics have been proposed. The two most commonly applied include, SIR (Susceptible, Infection, Recovered) and SERS (Susceptible, Infection, Recovered, Susceptible) models, which describe individuals through three mutually exclusive stages of infection (Giordano et al. 2020). It is however, important to note that these models only represent the epidemiological profiling of pandemics, future PHI must stress the need to create a wholistic approach in the management of infectious diseases, including consideration of population density and quality of housing.
The model projection in this paper suggests that outbreak prevention in informal settlements will do relatively little to prevent transmission of the pandemic, provided that 65% of the 4 million people living in Nairobi continue to reside in the informal settlement. This observation has been reinforced by previous studies on why any public policy in informal settlement cannot succeed, unless the issue of population density and quality of housing is adequately addressed (UN-HABITAT 2019). Informal settlements also often have higher levels of intra and intersocial mixing, poor environmental conditions, transient residence, and less regard to human well-beings that makes residents highly vulnerable to infectious diseases (Emina et al. 2011). The implementation of a blanket containment strategy was bound to have an acute negative effect on slum residents who live in makeshift single-roomed units made from corrugated iron or mud and often serve as the kitchen, bedroom, and sitting room for a multi-generational family. Our qualitative modeling is consistent with Gibson et al. (2019), who argue that lack of access to quality housing, and regular income has turned the residents into paupers who find themselves in the bustling cities. In short, public accountability has been compromised, thus, as projected by our model, control of community transmission might have not been possible using an intervention mechanism that does not take into account the socio-economic dynamics of the residents.
In regard to household air pollution (HAP), our modeling shows that under business-as-usual (before the strategy of containment), the movement of residents away from the nuclei (as illustrated in Annex 3a), would decongest households while at the same time maintaining social closeness, consequently, reducing the risk of establishing the pandemic through intra-house transmission. However, the trend changes with introduction of containment, as residents are compelled to swing (move) inwardly leading to sudden drop in the quality of indoor air. This strategy-induced behavior should be taken as a warning sign that if a PHI is to reach the WHO acceptable quality of air free of indoor pollutants and other hazardous substances, government regulations, and budgetary allocations should be accelerated to improve both indoor and outdoor air conditions. According to our model’s projection without addressing the inequalities and abject poverty, viability of an effective PHI in the foreseeable future is in doubt. Even for the COVID-19, for a downward trend in community transmission to be achieved, especially for asymptomatic cases, poorly ventilated housing structures in informal settlement should have been addressed. Otherwise, the scenario illustrated in Annex 3b will increase the vulnerabilities of residents due to stress on sanitary facilities.
However, if the preventive effect of containment and other social control policies reduces significantly due to civil disobedience by slum residents, the state might establish other alternative measures such as compulsory quarantine and total lockdown, which could become indispensable when the number of infected individuals exceeds the capacity of health care facilities. In the event that suppression of the slum residents by the state fails, and the scenario in Annex 3a remains intact, the lack of alternative means of survival compels the residents to rely on air quality-compromised lighting and cooking facilities. Our model shows that under the baseline scenario (without containment strategy), voluntary self-isolation would be effective. However, the caveat here is that the PHI system should be one that has the capability to detect and mitigate intrahousehold transmission from index cases to contacts.
The continually spiking percentage of transmission of COVID-19 infections in the country, despite instituting the containment strategy, suggests that there are other intervening factors. The effect of school closure, work-from-home, and other mobility restrictions compounded the challenges faced by people living in informal settlements. The assumption by the Kenyan Ministry of Health was that by “containing” people in their homes, they would then redirect investment towards quarantining those infected as an ultimate measure of controlling further transmission. However, asymptomatic cases that accounted for 80% of the infected population, unfortunately turn out to be a significant contributor to the transmission (Ing et al. 2020). The challenge, however, was the identification of such individuals, and especially in informal settlement where residents exhibit irregular migratory behavior. This lifestyle is a unique feature in slums. The residents exhibit pendulum-like swings in search of food, job opportunities, new networks, and escaping the scourge of hunger and domestic quarrels. The swing is also a sign of personal safety and security. Our model points to the potentially high transmissibility given the irregular micro-migratory behavior of the residents. Factors contributing to this susceptibility are many: the mode of transport is a concern since many residents rely on public means of transport that is characterized by crammed mini-busses and vans (matatus) often for long distances making this form of mobility a perfect vector for the spread of respiratory diseases. But even after the government announced countermeasures to curb the spread of the disease, still slum residents are inadvertently affected.
Finally, our analysis establishes that social safety nets, when used in combination with changes in the above policies, have the potential of mitigating transmission of future pandemics. As per our model projection, lack of social security measures such as health insurance coverage can be exacerbated through societal inequalities and job insecurities given that most of the residents in slum areas rely on daily livelihoods without pension. Social control measures instituted under the strategy of containment included casual workers being subjected to compulsory leave days, yet there was no guarantee that one would be recalled back after the pandemic is over. For those who are into the private sector, the majority are absorbed into low-earning, high-risk jobs such as, waste recycling, street vending, and artisanship. For some, especially those residing in major cities of Nairobi, Kisumu, and Mombasa, the state’s brutality executed through police force meant that residents violate social control measures in order to circumvent the containment rules and earn a living. In view of this behavior, we observe that for future pandemics, the PHI strategy should be integrated with these patterns of livelihoods. The strategy should also entail a social sensitivity element such as gender, age, and social class.
These social considerations should be an integral part of the future response strategy to pandemics. Our observation concurs with JP Morgan’s (cited in Mail online 2020) findings that the enforcement of lockdown strategies did not necessarily lead to reduction in the rate of transmission of COVID-19. There seem to have been “other” pre-existing social, economic, and political conditions contributing to the spikes. Related to this “other” factor is the question of socio-economic injustice. The declaration by the Ministry of Education for all schools and colleges to shift to online learning as part of the containment strategy was yet another burden to the slum residents. Previous studies have clearly shown how the Kenyan education system perpetrates inequalities across the entire ecosystem—staff, facilities, and equipment (Alwy and Schech 2007). It should, however, be noted that, although previous studies show strong correlation between closure of schools and workplace and significant reduction in the transmission of influenza (Koo et al. 2020), our model projection points to the contrary; enforcement of such draconian strategies could actually trigger structural inequalities. In general, our model suggests that any PHI strategy which excludes social geometry either directly or indirectly is bound to be rejected and is also subject to inequity. This failure in strategy is exacerbated by the design of the current PHIs. What is perhaps missing from the current PHI strategy is a context-specific structure that is more explicit on the resident’s social geometry building blocks—location, distance, and direction.
Simulating Decision in Selecting the Most Effective PHI Strategy
This paper also explains how the variables (henceforth referred to as ‘risk factors’) in Annex 5 would be affected by various PHI strategies (containment, lockdown, and social pendulum) on pairwise ranking technique. The severity of the ‘risk factors’ is based on the discourse analysis as outlined by the Indicator Development for the Surveillance of Urban Emergencies (IDSUE) classification (USAID/Concern World Wide 2014). In our modeling, the ranking would then facilitate decision making in selecting the most effective strategy in managing future pandemics. On this technique, the most effective strategy is one with the highest frequency of the ‘Green’ code, while the ‘Red’ would symbolize inappropriate or potentially harmful strategy. To be precise, for the three strategy options, the 16 items were compared in the decision matrix (Annex 5), such that the rankings generated the prescribed strategy option.
The number of times a ‘risk factor’ had been found to be most affected by a particular ‘reagent’ (strategy option) was determined by counting the number of times a distinct color appeared in the decision matrix (“Red,” “Yellow,” or “Green”). Each one of the ‘reagents’ was mutually exclusive. The assumption here is that the ‘reagent’ would be introduced at different times to the same group of people. Residents’ reaction would vary according to the reagent’s effect. The outcome of the decision matrix (Annex 5) facilitated the construction of Table 1, with each ‘risk factor’ being compared against the three strategy options. Thus, ‘containment’ was compared first with ‘lockdown.’ We deduced that ‘containment’ induced the least (1 out of the possible 16), ‘high risk factor’ compared to ‘lockdown,’ which generated the highest (13 out of possible 16) ‘high risk’ factors followed by ‘social pendulum’ with three ‘high risk’ factors. In line with our model projection, if movement restrictive strategies, such as lockdown and containment, are instituted, most of the items would indicate ‘high risk’ and ‘medium risk,’ respectively. However, urban infrastructure and slum collectivism seem not to trigger ‘high risk’ on the same strategy. Interestingly, ‘infrastructure,’ ‘collectivism,’ and ‘asymptomatic’ factors would actually change to “high risk” if the social pendulum was to be adopted as the strategy option for managing COVID-19 and other unforeseeable pandemics. The strategy option recording the highest number of risk factors, is considered to be the least preferred option. In this case, ‘lockdown’ appears to record the highest (13) in the decision matrix than any other strategy option (Table 1). Hence, the public health officials and government authorities would be advised to be cautious of a ‘lockdown’ as a PHI strategy option.
Table 1 Results of simulating decisions for the PHI strategy options In line with our model projection, ‘lockdown’ strategy option was considered to be the most problematic. From Table 1, it is understood that although the social pendulum option generated the highest number (12 out of 16) of ‘low risk’ factors, its adoption would have to consider three structural conditions:
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if it is adopted as a solitary PHI strategy, it is likely to put pressure on existing outdoor infrastructure (watering points, roads, and other public amenities), unfortunately, leading to outdoor pollution;
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the epidemiological management of the asymptomatic condition among the residents will be crucial. As illustrated in the decision matrix (Annex 5), this ‘risk factor’ is likely to be highest for both ‘containment’ and ‘lockdown’ strategies; and
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Although, the asymptomatic factor, would indicate ‘medium risk’ for social pendulum strategy, this model outcome points to the difficulties that are likely to be encountered by public health officials in the surveillance and detection of “hidden” cases in densely populated areas.
In the event that all the three strategy options fail to curb community transmission through asymptomatic individuals, a combination of interventions should be integrated in the PHI strategy, including surveillance, school closure, and workplace spatial distancing. Our modeling outcome here concurs with a recent study by Qun and his colleagues, who recommended that in situation of a persistent asymptomatic conditions, potential secondary control-response strategies should be part of the intervention (Qun et al. 2020). In line with our model projection, the prevalence of future pandemics will be mainly driven by the resident’s access or lack of access to a combination of both public health facilities (sanitation and air quality), socio-economic safety nets, and appropriate urban planning that accommodates the unique behavioral patterns of people living in informal settlements.
Given the conditions under which slum residents live we consider what ‘containment’ means for the vulnerable population in the informal settlements. In order to look more systematically at the question of a pandemic management in informal settlement, a new concept is introduced here, that of ‘social pendulum.’ The idea of ‘social pendulum’ is based on both the principles of physics (time, space, location, distance, and direction) and social science principles (relationships, social space, solidarity, and shareability). The swing symbolizes the residents’ coping strategies. The ‘pendulumic’ analogy we propose in this paper forms part of the alternative PHI strategy developed in the following section.
Social Pendulum: An Alternative Strategy?
The qualitative modeling of an alternative framework in the foregoing section indicates that such constructs can shed some light on the human behavior and what type of PHI strategy would be ideal for the urban informal settlements.
The ‘urbanites’, and especially the slum residents’ (henceforth referred here as slumites) behavior and cultural values strongly influence the acceptability of any PHI strategy. For instance, individuals or groups who are socially close to each other will handle the pandemic differently than those who are socially distant. The PHI strategy proponents may decide to follow this pattern of behavior or simply impose a generic scheme designed without considering the contextual dynamics. This decision determines the outcome of a strategy. In this paper, we conceptualize the actions and behaviors of both the slumites and the public health officials as changes in social geometry. In this light, ‘containment’ strategy that was instituted by the Kenyan government to prevent transmission of COVID19 is viewed as a conflict that is caused by disrupting social relations. In the social space parlance, such changes are labelled deviant interventions because they alter the social geometry balance of power in a community. On this account, it is plausible to argue that ‘containment’ strategy disrupted the structure of slumites in different directions, location, and distance. As observed by Black (2011, pp. 6), “the severity of this disruption is a direct function of the magnitude of the change.” On the basis of this explanation, it is reasonable to observe that the containment strategy gave rise to different forms of social geometries. It is therefore necessary to analyze the importance of these socio-geometric (im)balances with the aim of reimagining an effective PHI strategy in the management of future pandemics. So, what should constitute an effective PHI strategy in urban slums?
To address this question, our study suggests that an effective PHI should aim at (1) closing the swing loop—in short, provide the needed basic requirements to the residents, including watering point, movement corridors, sanitizers, and indoor ventilation facilities; and (2) intervene just-in-time and space (JITS). JITS approach to the management of public affairs, including pandemic would aim at minimizing overcrowding by ensuring that the PHI is provided wherever the immigrants are found along the swing pathway. However, such a strategy should be mindful that intervening on the basis of JITS may not necessarily be the panacea for preventing the transmission of a pandemic, because this is a logistic intensive process that depends on the efficiency of the existing public health infrastructure, road connectivity index, and quality of housing. In the world of public policy, lack of these facilities may actually lead to spikes in transmission of an infectious disease, leading to a potential humanitarian disaster. Previous studies that have examined other control measure models beyond the draconian ones (containment and lockdown) recommend effective monitoring and surveillance capabilities (Ng et al. 2020).
Yet, models that promote solidarity among people within same socio-economic stratum such as cooperatives have been found to promote inclusion (Borda-Rodriguez and Johnson 2020). In the current study, we utilize Black’s (2011), four socio-geometric techniques (form, style, quantity, and multidimensionality of social relations), to re-imagine an effective PHI strategy for managing pandemics. Form—the analysis and the design of an effective PHI strategy should allow the stakeholders to see how the relationship fits together and how the intervention serves the intended function of preventing transmission of the pandemic (COVID-19). Style—ideally, the explanation and the design of an effective PHI strategy should be able to account for the unintended consequences of the intervention. An important consideration is that when containment of collective communities in the informal settlement is intensified, hence, increasing the flow of people indoors (see Annex 3a), the risk of transmission goes high. To avert this, the PHI system should have the capability to trigger outward swings (see Annex 3b), which eventually increase social closeness of the slumites. This system thinking approach concurs with our model prediction that the closer the social distance, the more likely the homogenous group will collaborate with public health officials in instituting the PHI. As earlier illustrated in our modeling outcome (Annex 3b), spatial distance has minimal influence on survival of slum communities, because they can still retain connections through social informal networks.
Quantity—One of the principles of ethnomethodology is that the interpretation of the intervention should be bestowed upon the size of the affected population. Related to quantity is the last technique—multidimensionality of relationship—an understanding of the urban socio-cultural structures and their functions in the community helps the interventionists to make sense of people’s preferred approach to solving their problems. Therefore, in analyzing and designing an appropriate PHI strategy, caution must be made to ensure no new problems are created. Similarly, the egalitarian social organization, common among the slum communities can pose a challenge in managing intergroup dynamics. To make sense of the intergroup dynamics, Black (2004) analytical framework provides five elements that we think are useful in our new proposed social pendulum framework: (1) interventions should ensure high intimacy and interdependence between members; (2) the intervention should not alter social geometries, groups should maintain the social closeness; (3) the intervention should be functionally interdependent; (4) create or sustain cultural closeness among the population; and (5) groups can be separated by an intermediate degree of relational distance.
The above criterion is key in ensuring that the group configuration is intact and that the public health interventionists build up on the existing social geometries. However, with the complex nature of urban slums, it is not feasible to have a ‘one-fit-all’ approach to PHI. In the foregoing discussion, the profile of slumites reveals that their pattern of livelihood is erratic (unpredictable), and their coping mechanisms and livelihood activities are multi-directional (see Annex 3a, b). As a result, the residents can hardly follow a systematic order of events. Rather, their lifestyle maintains constant swings. Worse still, the swings (movement) are not linear, but the day-to-day needs pushe them to swing between their makeshift houses and the “unknown” destinations, and back. In this paper, the swings represent the socio-economic needs of the residents, while the makeshift houses represent the fixed points akin to the massless rod of the physical pendulum. Hence, we coin the notion ‘social pendulum,’ figuratively to represent the PHI structure that is anchored on realities of the target population. In our conception of the new framework, the swings perform three major functions in the new configuration of the slum ecosystem:
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(i)
The idea of ‘social pendulum’ allows slumites to ‘swing’ freely depending on the time, available, spatial space, location, distance, direction, and access to livelihood opportunities;
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(ii)
The swings symbolize the residents’ coping strategies against socio-economic shocks and health risks associated with high concentration of people within a limited spatial space; and
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(iii)
The swings allow the community to maintain social networks and identity.
From this characterization, it is plausible to observe that an effective intervention should then be one that allows diffusion of the population away from the ‘community nuclei.’ Essentially, our proposed model offers a canal pathway for decongesting the spatial space, at the same time sustaining social closeness of the slumites for their socio-economic survival. This ‘pendulum-like’ movement (see Fig. 6) of people as they seek livelihood opportunities has the potential of creating indoor spatial space, which in turn improves indoor ventilation. This approach to the management of pandemics in urban slums can be helpful in lessening the ecological exigency on sanitary facilities. These socio-environmental conditions are known to prevent spread of respiratory illness (Dianati et al. 2019). Figure 6 summarizes the new proposed analytical framework for informing PHI strategy.