| Literature DB >> 35194401 |
Stephan Moonsammy1, Temitope D Timothy Oyedotun2, Donna-Marie Renn-Moonsammy3, Temitayo Deborah Oyedotun4, Nasrudeen Ally2, Oluwasinaayomi Faith Kasim2, Ayomide Famewo5.
Abstract
The novel COVID-19 pandemic has disrupted the functioning of solid waste management globally as households experience an increase in their waste and a change in waste collection services. This study presents a statistical model looking at the impacts of COVID-19 on household waste and waste collection services and the prevalence of self-disposing in response to these impacts. Qualitative household data were collected from Guyana and Nigeria looking at household perspectives on their waste management issues since the emergence of COVID-19. Statistical models were developed using limited-dependent binary logistic regression. The models showed for each country, different factors contributing to the likelihood of self-disposing. For Guyana, the change in waste collection schedule and the household proximity to landfills increases the likelihood of self-disposing while in Nigeria, the increase in household waste increases the likelihood of self-disposing. The results also showed that households who regularly engage in recycling activities are less likely to self-dispose. The study concludes that COVID-19 has disrupted household waste disposal and had contributed to increasing instances in self-dumping. COVID-19 seems to be fostering the informal waste sector which may require a shift in the current operation and policies for the solid waste management sector. © Springer Japan KK, part of Springer Nature 2021.Entities:
Keywords: COVID-19; Informal waste sector; Municipal solid waste; Self-disposing
Year: 2021 PMID: 35194401 PMCID: PMC8034766 DOI: 10.1007/s10163-021-01225-4
Source DB: PubMed Journal: J Mater Cycles Waste Manag ISSN: 1438-4957 Impact factor: 2.863
Descriptive characteristics of the exogenous variables
| Variable | Description |
|---|---|
| Increase in household waste | Households observed a notable increasing household waste |
| Reduced Services | A reduction in schedule of municipal waste collectors was observed by households |
| Proximity to Dump | Household located near to an established or unregulated dumping site |
| Populous Municipality | Household located in the most populous municipality in the data |
| Practice Recycling | Household engages in re-use, recycling or upcycling activities |
Models consists of qualitative exogenous variables only
Characteristics of Household solid waste management since COVID-19
| Guyana | Nigeria | |
|---|---|---|
| Noticed increase in household waste since COVID-19 | 64.8% | 59.6% |
| Household waste volume doubled since COVID-19 | 45.7% | 50.1% |
| Noticed change in municipal waste collection services since COVID-19 | 23.6% | 63.9% |
| Municipal services scheduled once a week | 63.6% | 75.9% |
| Household engages in more recycling activities since COVID-19 | 46.8% | 16.5% |
| Households in data located in the most populous municipalities | 51.4% | 20.4% |
| Households in data with landfill or dumpsite in community | 28.2% | 30.4% |
| Households that engages in self-disposing since COVID-19 | 31.0% | 31.9% |
Measured as a percentage frequency of the sample; the values reported represented the largest share of the sample
Binary logistic regression models on self-disposal of household waste
| Model 1 | Model 2 | |
|---|---|---|
| α | − 0.434 (0.341) | 1.904** (0.737) |
| Increase in household waste | 0.325 (0.368) | 0.938** (0.293) |
| Change in collection schedule | 1.864*** (0.378) | − 0.335 (0.267) |
| Proximity to landfill | 0.688* (0.362) | − 0.142 (0.234) |
| Practice recycling | − 0.724** (0.341) | − 1.557*** (0.363) |
| Located in Georgetown | − 0.486 (0.341) | – |
| Located in Lagos | – | − 0.942** (0.415) |
| Located in Oyo State | – | 0.033 (0.312) |
| Cox and Snell R Square | 0.205 | 0.312 |
| Nagelkerke R Square | 0.299 | 0.438 |
Hosmer and Lemeshow | 0.523 | 0.615 |
Model 1 presents the analysis for the LOGIT model for Guyana and Model 2 presents the analysis for the LOGIT model for Nigeria; values in () are the std. errors for the coefficients
*Indicates 10% significance; the Cox and Snell and Nagelkerke R Square and Hosmer and Lemeshow test are goodness of fit diagnostic measures
**Indicates 5% significance
***Indicates 1% significance