The study, led by Md Ayatullah Khan and Farhana Hoque of Khulna University together with colleagues at the University of Chittagong, surveyed 450 slum household heads using a cluster-based household survey across three purposively selected wards — 12, 21 and 31 — of the Khulna City Corporation, an area home to a significant share of Bangladesh’s slum dwellers. Rather than treating pandemic hardship as a single outcome, the researchers modelled it as a chain of linked events: employment loss leading to income loss, income loss driving shortages of daily necessities, and those shortages in turn forcing families to deplete savings and, ultimately, sell off assets. Each link in that chain was analysed separately, allowing the team to trace precisely how one form of deprivation raised the odds of the next.

The statistical toolkit combined descriptive measures — means, standard deviations and percentages — with inferential techniques including t-tests, chi-square tests and a binary logit model. The binary logit approach, a standard method for modelling outcomes with two possible states, allowed the researchers to estimate how demographic and socio-economic characteristics changed the probability that a household experienced each stage of the loss spiral. This design matters because it moves the analysis beyond simple description: it identifies which characteristics of households statistically predicted each downstream loss, controlling for the other variables in the model.

The demographic profile that emerged from the survey is strikingly consistent with the structure of urban informal labour in South Asia. The majority of household heads were male, had little formal education, and worked in daily-wage or informal occupations — day labourers, market vendors, rickshaw pullers, auto drivers and housemaids. These are precisely the jobs that vanished overnight when lockdowns were imposed. A rickshaw puller cannot work from home; a market vendor cannot sell vegetables to customers who are ordered to stay indoors. Unlike salaried workers in the formal economy, informal workers in Bangladesh typically have no contracts, no severance pay and no unemployment insurance, so the loss of work translated immediately and completely into the loss of income.

And that translation was the engine of the spiral. The analysis found that employment loss strongly predicted income loss, which in turn significantly increased the odds that a household would face shortages of daily needs — food, medicine and other essentials. Once a family’s income stream was severed, its thin financial buffers eroded rapidly. Savings loss followed, and beyond savings came asset loss: the sale of livestock, utensils, mobile phones or building materials that represented years of accumulated economic security. In the vocabulary of development economics, these households were not merely made temporarily poorer; they were pushed backward along the asset ladder that normally protects poor families from falling into chronic poverty.

The binary logit results also isolated the risk factors that made some households more likely to suffer than others. Older age of the household head, low levels of schooling, pre-existing indebtedness and living in rented accommodation all emerged as key predictors of pandemic-induced losses. Each of these factors has a clear mechanistic interpretation. Older household heads face both reduced earning capacity and greater health risks in a pandemic, making them less able to seek alternative work. Low schooling restricts the range of jobs a person can take, trapping workers in the most pandemic-exposed occupations. Indebtedness means that any income interruption immediately triggers pressure from lenders, forcing distress sales. And renters, unlike owners, must continue paying for shelter even when their income has stopped, converting every week of unemployment into a mounting liability.

The authors interpret these findings through the lens of the livelihood-vulnerability framework and the concept of the poverty trap. In this view, poverty is not simply a low level of income but a dynamic process in which shocks interact with a household’s limited assets, weak institutions and precarious employment to produce self-reinforcing decline. A pandemic lockdown is exactly the kind of shock that such households are least equipped to absorb: they hold few liquid assets, they lack access to formal credit, and their labour — their principal asset — is the very thing the lockdown suspends. The result is a vicious circle in which each loss makes the household more vulnerable to the next, and recovery becomes progressively harder without external intervention.

The Khulna findings echo a broader pattern documented across the Global South during the pandemic. Studies of informal settlements in Bangkok, Kampala, Rio de Janeiro, Nairobi and Santiago de Chile all recorded steep employment and income losses among slum residents, along with food insecurity and disrupted access to healthcare. Research in Dhaka and elsewhere in Bangladesh reported income drops of as much as 80 percent among the urban poor during the early lockdowns. What the new study adds is the explicit modelling of the loss cascade itself — demonstrating statistically that the stages of deprivation are not parallel symptoms of the pandemic but sequential consequences, with employment loss as the upstream driver and asset loss as the terminal stage.

From this causal structure, the authors derive a set of policy recommendations that are notable for their sequencing. Because employment loss sits at the head of the spiral, interventions that prevent job loss or rapidly restore earning capacity deliver the greatest downstream benefit. The study recommends a targeted skills development programme and the creation of formal employment linkages for informal workers, alongside legal and institutional protections for informal work — a sector that employs the vast majority of urban workers in Bangladesh but operates largely outside the reach of labour regulation. Such measures address the structural fragility that made slum dwellers so exposed in the first place.

For households already caught in the spiral, the authors recommend immediate cash transfers, debt relief and rental support. Cash transfers replenish the income stream directly, allowing families to buy food without selling assets; debt relief halts the distress-sale dynamic that converts temporary hardship into permanent impoverishment; and rental support keeps families housed while they rebuild. The logic is to interrupt the cascade at its weakest link before the losses compound. As the world confronts future pandemics, climate shocks and economic crises — all of which hit informal urban settlements hardest — the Khulna study offers a sobering lesson: protecting the poor requires not just aid, but aid delivered early enough, and targeted precisely enough, to stop the spiral before it starts.

Subject of Research: Socio-economic drivers of pandemic-induced employment, income, savings and asset losses among urban slum dwellers in Khulna, Bangladesh

Article Title: Drivers of pandemic-induced losses and shortages among urban slum dwellers: a case from Bangladesh

Article References: Khan, M. A., Hoque, F., Islam, K. R., & Yeasmin, K. M. (2026). Drivers of pandemic-induced losses and shortages among urban slum dwellers: a case from Bangladesh. SN Social Sciences, 6(10), Article 444. https://doi.org/10.1007/s43545-026-01729-6

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01729-6

Keywords: COVID-19, urban slums, Bangladesh, informal employment, income loss, poverty trap, livelihood vulnerability, binary logit model, cash transfers, Khulna, food insecurity, debt relief

The study was led by Sabiya Akhter of Khulna University, working with Md. Akramul Islam and Shaikh Magfur Rahman. In December 2021, the team collected 22 soil samples from the top 15 centimeters of soil across Gangarampur Union in Batiaghata Upazila, Khulna district. Sampling points were laid out on a systematic grid roughly one kilometer apart to ensure consistent geographic coverage, and at each point five subsamples were gathered at random and blended into a single composite sample. Portable GPS devices recorded the exact coordinates of every location, allowing the chemical results to be tied precisely to the landscape. The samples were air-dried in the shade, gently crushed, sieved to two millimeters to remove stones and root fragments, and shipped to the Soil, Water and Environment Discipline laboratory at Khulna University for analysis.

The analytical suite covered the macronutrients that govern crop growth: total nitrogen, available phosphorus, available sulfur, available potassium, available calcium and available magnesium, along with soil organic matter. Total nitrogen was measured colorimetrically, a choice the researchers justify because available nitrogen forms fluctuate wildly with environmental conditions at the moment of sampling, whereas total nitrogen represents the stable reserve of the soil and is widely regarded as a reliable fertility indicator. Available phosphorus was extracted with sodium bicarbonate solution using the Olsen method and quantified with the molybdophosphoric blue color technique. Sulfur was assessed by turbidimetry, with barium chloride generating the turbidity that a spectrophotometer reads at 420 nanometers. Potassium, calcium and magnesium were extracted with neutral ammonium acetate, and organic carbon was determined by the classic Walkley and Black wet oxidation method, converted to organic matter using the conventional Van Bemmelen factor of 1.724.

The numbers that emerged reveal a soil system under acute strain. Total nitrogen ranged from a mere 0.001 percent to 0.016 percent, with a mean of 0.0103 percent, and every sample landed in the very low category. Organic matter fared somewhat better, spanning 0.38 to 4.19 percent with a mean of 2.47 percent, but roughly half the samples still fell into the low class. Available phosphorus was the most erratic nutrient of all, ranging from 2.17 to 113.39 parts per million with a coefficient of variation of 136.7 percent, the highest of any measured parameter, and about half the samples were classified as low. Sulfur, by contrast, was remarkably consistent and overwhelmingly abundant, with 77.27 percent of samples in the very high category and a modest coefficient of variation of 34.28 percent. Potassium and magnesium were rated very high in every sample, while calcium mostly sat in the optimum range.

To turn these point measurements into a landscape-scale picture, the team used inverse distance weighted interpolation within ArcGIS 10 software. This technique estimates values at unsampled locations by weighting nearby measurements more heavily than distant ones, producing smooth nutrient distribution maps across the union. The researchers deliberately chose this method over more sophisticated geostatistical approaches such as kriging because, with only 22 sampling points, the reliability of variogram modeling degrades and simpler interpolation can actually outperform it. The resulting maps show nitrogen uniformly in the very low class across the entire area, phosphorus concentrated in the very low and low classes, sulfur exceeding 45 parts per million throughout, and potassium above 0.375 milliequivalents per 100 grams everywhere. Magnesium mirrored potassium, while organic matter clustered in the low to medium range.

The nutrient index, a weighted scoring system that condenses the frequency distribution of samples into a single fertility rating, confirmed the pattern. Nitrogen scored 1.0, the lowest possible value, and phosphorus scored 1.95, placing it in the medium band. Sulfur reached 5.31, potassium and magnesium both hit the maximum of 6.0, calcium scored 3.31, and organic matter registered 2.4. In practical terms, the soils of Gangarampur are starving for nitrogen and phosphorus while drowning in sulfur, potassium and magnesium. This imbalance matters because applying fertilizer blindly, without knowing which nutrients are already plentiful, wastes money, pollutes waterways and can even suppress yields through nutrient antagonism.

The reasons behind this skewed profile are rooted in the region’s geography and history. The study area sits within the high Ganges alluvial floodplain and the Ganges tidal floodplain, where periodic flooding with tidal water delivers seawater-derived sulfur, potassium and magnesium directly to the fields. Coastal soils formed from alluvial and deltaic deposits also contain potassium-rich minerals such as feldspar, mica and illite, which weather slowly and release potassium into the soil solution. Nitrogen, however, has no such geological subsidy. The authors attribute its collapse to excessive continuous cultivation, rapid decomposition of organic matter in the hot humid climate, minimal application of manure or compost, and gaseous losses of ammonium nitrogen to the atmosphere. With mean annual rainfall of 1,693 millimeters, leaching and denitrification strip what little mineral nitrogen the soil can hold.

Phosphorus deficiency has its own chemistry. The alkaline, calcareous coastal soils tend to lock phosphorus into insoluble forms that plant roots cannot access, a process known as phosphorus fixation. Salinity intrusion from the sea, an escalating problem in the Khulna region as sea levels rise and upstream freshwater flows decline, further suppresses phosphorus availability. Previous work in coastal Bangladesh, including surveys dating back to the 1980s, has consistently documented nitrogen deficits in saline zones, and the new maps confirm that decades of high-yielding variety rice cultivation, sustained by heavy applications of urea, triple superphosphate and muriate of potash, have failed to rebuild the underlying nutrient capital. Organic matter, the engine of soil fertility, remains low across much of the area, a decline the researchers link to erosion, altered land use including shrimp farming, and the removal of crop residues.

The correlations among nutrients add another layer of insight. The analysis found a positive relationship between nitrogen and calcium, but negative correlations between nitrogen and potassium, and between sulfur and magnesium. Such antagonistic patterns suggest that the abundant cations supplied by tidal flooding may interfere with nitrogen uptake or retention, complicating any simple fertilization recipe. The authors argue that the region’s excessive precipitation, driving erosion and leaching, combined with the sandy fraction inherited from the parent material, underlies the generally poor fertility rating for nitrogen and phosphorus. Their central recommendation is unambiguous: nitrogen nutrition should be the top priority, with careful attention to phosphorus, before any crop planning in the region.

The study is candid about its limits. Twenty-two samples taken from a shallow 15-centimeter depth cannot capture every nuance of spatial variability across a landscape of nearly 38 square kilometers, and the findings should be generalized with caution. The authors call for long-term monitoring to track how soil fertility changes over time, the integration of remote sensing and geostatistics to sharpen future maps, and the coupling of soil data with crop performance data to enable truly targeted nutrient management. Even so, the work delivers a practical tool for farmers, extension services and policymakers in a region where agriculture accounts for the majority of livelihoods and cropping intensity runs at roughly half the national average. By showing exactly where nitrogen must be rebuilt and where potassium and sulfur can be left alone, the nutrient atlas offers a blueprint for cutting fertilizer waste, reducing environmental degradation and steering the coastal fields of Khulna toward the sustainable, food-secure future that both the global sustainable development goals and local families demand.

Subject of Research: Spatial assessment of soil macronutrient status and fertility in coastal agricultural soils of Khulna, Bangladesh

Article Title: Spatial distribution of soil macronutrients and nutrient index for sustainable agriculture in the Khulna region of Bangladesh

Article References: Akhter, S., Islam, M. A., & Rahman, S. M. (2026). Spatial distribution of soil macronutrients and nutrient index for sustainable agriculture in the Khulna region of Bangladesh. Discover Soil, 3(1), Article 137. https://doi.org/10.1007/s44378-026-00296-9

Image Credits: AI Generated

DOI: 10.1007/s44378-026-00296-9

Keywords: soil fertility, macronutrients, nitrogen, phosphorus, nutrient index, spatial distribution, GIS mapping, Bangladesh, coastal agriculture, sustainable agriculture, soil organic matter, Khulna