Akila Muthalagu1, Yang Lian2, Rekha M Ravindran3, Asif Qureshi  This email address is being protected from spambots. You need JavaScript enabled to view it.1,4

1 Department of Civil Engineering, Indian Institute of Technology Hyderabad, Kandi, TS 502285, India
2 Indian Institute of Tropical Meteorology, Pune, MH 411008, India
3 State Health Systems Resource Centre, Department of Health and Family Welfare Thycaud, Thiruvananthapuram, Kerala 695014, India
4 Department of Climate Change, Indian Institute of Technology Hyderabad, Kandi, TS 502285, India


Received: August 9, 2023
Revised: October 11, 2023
Accepted: October 27, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.4209/aaqr.230191  

Cite this article:

Muthalagu, A., Lian, Y., Ravindran, R.M., Qureshi, A. (2024). Impacts of Floods on the Indoor Air Microbial Burden. Aerosol Air Qual. Res. 24, 230191. https://doi.org/10.4209/aaqr.230191


  • The impact of floods on microbial quality of indoor air and vicinity was assessed.
  • Microbial concentrations were indoor air of flooded houses were 3x than control.
  • Outdoor air and soil contributed to the bacterial burden in the flooded indoor air.
  • Indoor surface dust and outdoor air contributed to the flooded indoor fungal burden.
  • Antibiotic resistant bacteria detected in chlorinated well water, and indoor air.


Floods create a conducive environment for the proliferation of microbes in the indoor air by providing nutrients and moisture and by introducing new microbes from outdoors to indoors. Thus, it is important to better understand the level of proliferation and the characteristics of microbes in the indoor air of flooded built environments. In this work, we address these aspects in a flooded environment in India and investigate the changes in the indoor air microbial burden by comparing with the control (non-flooded) houses. Flooded houses within one month of water recession were compared with control houses. Microbes (bacteria, fungi) were characterized and endotoxins were quantified. Microbial concentrations were significantly higher in flooded houses than the control houses (p < 0.05). The potential infectious bacterial genera Pantoea, Acinetobacter, and fungal genera Aspergillus and Penicillium were found dominant in the indoor air of flooded houses. Though these fungal genera were also present in the control houses, concentrations were higher (p < 0.05) in the flooded houses. Multivariable regression analysis revealed that indoor air microbial burden was significantly and positively associated with outdoor air and outdoor soil. Further, antibiotic resistant bacteria (ARB) were found in both indoor air, and outdoor water sources (wells) of flooded houses. In our chlorine tests, the bacteria showed resistance to concentrations above 100 ppm, far exceeding those found in national and international guidelines. Bacteria were resistant to common antibiotics such as penicillin and ciprofloxacin.

Keywords: Floods, Infectious diseases, Antibiotic resistant bacteria, Chlorine resistance, Built environment


Floods are among the most common and widely reported natural disasters. They are often followed by compromised hygienic conditions in the human habitat. Floods lead to the creation of damp conditions inside houses, which leads to an increase in the growth of molds (Barbeau et al., 2010) and pathogenic microbes (Solomon et al., 2006). Floods may also lead to a transfer of microbes from the outdoor environment to the indoor environment (Adams et al., 2015) via flooded water, inflow of outdoor air, transfer of soil through, for example, footwear of inhabitants, and even through the bioaerosols created by indoor showers or faucets (Prussin and Marr, 2015). Further, enhanced water flows may enable the transfer of microbes from farther locations, such as inundated water/wastewater treatment plants, sewage systems, clinics and farmlands, to streams and ponds (Andrade et al., 2018) and from streams and ponds, or directly, to the immediate built environment such as wells and courtyards. These may subsequently be transferred to the indoor environment.

Studies reveal floods' role in escalating microbial burden. After the 2013 Colorado floods, indoor fungal concentrations tripled compared to non-flooded homes (Emerson et al., 2015). Flooded houses had higher endotoxin levels linked to adverse health effects (Solomon et al., 2006). Un-remediated homes after the Cedar River flood in 2008 showed elevated bacteria and endotoxin concentrations, leading to health issues (Hoppe et al., 2012). Media beyond air, such as water, were also impacted. Flood-affected homes had Escherichia coli and Enterococci in faucets and taps (Phan and Sherchan, 2020), contributing to disease outbreaks (Kouadio et al., 2012).

While qualitative and quantitative changes in bacterial and fungal communities in and around the moisture-damaged buildings (i.e., the built environment) have been reported frequently (Hoppe et al., 2012; Jayaprakash et al., 2017), fewer studies have quantitatively assessed the association of detected microbial concentrations with home characteristics (home ecology parameters such as human occupancy and activities, ventilation and type of flooring), and the potential sources of these indoor air microbes. It is moreover important to note that the majority of studies on indoor air in flood damaged buildings were conducted primarily in the United States (Hoppe et al., 2012; Phan and Sherchan, 2020; Solomon et al., 2006), and much less in parts of the world which are prone to flooding such as Brazil, India and other parts of Asia.

India, one of the most weather-affected countries, faces recurrent floods with increasing intensity (Roxy et al., 2017). However, indoor microbial air quality in flood-affected Indian houses lacks study. Existing research concentrates on regular buildings (Akila et al., 2020; Kumar et al., 2018; Priyamvada et al., 2018; Sharma, 2018), leaving flood impacts unstudied.

We investigate floods' role in microbial burden and endotoxin levels in indoor air using Kerala's 2018 floods as a case study. Kerala experienced 42% above-normal rainfall (Government of India, 2018), causing extensive damage and displacement. Previous research identified contamination in soil and water (Jaya Divakaran et al., 2019; Shankar et al., 2021), but indoor environments remain unexplored. Our study characterizes indoor and outdoor air, benchmarking flood-impacted homes against controls. We analyze multiple media to trace microbial sources and quantify endotoxin levels. Additionally, we test for antibiotic-resistant bacteria presence and assess chlorination's effectiveness in well disinfection.


2.1 Sampling

2.1.1 Location

Sampling was conducted in the Kadapara and Parumala villages of the Pathanamthitta District (9.2601°N, 76.9643°E) (Fig. 1). Pathanamthitta was one of the worst affected districts of Kerala during the August 2018 extreme rainfall event (Kritika, 2018). Pathanamthitta received 117% excess rainfall, leading to large scale flooding and evacuation of inhabitants (Ameerudheen, 2020). Pamba and Manimala rivers were the major sources of flooding.

Fig. 1. Study area and sampling locations. (i) Spatial distribution of rainfall anomaly (%) over India during the massive rainfall event (August 8–10, 2018) in Kerala. The insert image represents anomalous rainfall over the state of Kerala (ii) Samples collected from flooded and non-flooded houses from Kadapra and Parumala villages from Pathanamthitta district, Kerala, India.Fig. 1. Study area and sampling locations. (i) Spatial distribution of rainfall anomaly (%) over India during the massive rainfall event (August 8–10, 2018) in Kerala. The insert image represents anomalous rainfall over the state of Kerala (ii) Samples collected from flooded and non-flooded houses from Kadapra and Parumala villages from Pathanamthitta district, Kerala, India.

Samples (indoor and outdoor air, outdoor soil, indoor surface dust, indoor tap water, and outdoor well water) were collected from twenty-one flood-affected houses and four non-flooded houses (control) from the study region. Control houses were not flooded due to site elevation. Sampling was conducted within a month after the floods. During flooding, the water level in flooded houses reached approximately 66–178 cm above ground level. Each of the houses had outdoor water wells. These wells provide water for cleaning, washing, and other domestic purposes, excluding drinking. After the floods, the District Health Department, with community health volunteers' help, chlorinated the well waters using bleaching powder (powdered calcium hypochlorite). Residents reported that bleaching powder was added to each well, and this process was conducted twice in the one month preceding our sampling.

2.1.2 Bioaerosols collection

Indoor air sampling was conducted in the living room at the height of 1.5 m above ground level. Immediately following the indoor sampling, the corresponding outdoor air was also sampled.

Viable bioaerosols were collected in 90 mm petri dishes (Tarson USA) placed on a single-stage cascade impactor with 400 holes with a size of 0.25 mm (BioStage single-stage sampler, SKC, USA) (Park et al., 2010). Samples were collected by drawing the air at the flow rate of 28.3 L min1 for 2 min (Akila et al., 2020). Fungal aerosols were collected on potato dextrose agar (PDA), and bacterial aerosols were collected on tryptic soy agar (TSA) and each sampling was carried out for 2 min separately. After every sampling, sampler was cleaned with 70% ethanol to avoid carry-over contamination (Akila et al., 2020).

After sampling, PDA and TSA plates were incubated as described earlier (Akila et al., 2020, 2018). The concentration of microbes was reported as colony-forming units per cubic meter of air (CFU m3). After the incubation period, inoculated plates were manually analyzed, and colonies that were different in morphology were used for further analysis.

For endotoxin analysis, particulate matter from the air was collected on a 47 mm diameter GF/A Whatman glass microfiber filter paper, using a Whatman filter holder connected to the pump. Air sampling was carried out for 60 min at the flow rate of 26.3 L min1 (Akila et al., 2020). An airtight 60 mm petri dish (Tarson USA), was used to store the samples. Immediately after sampling, they were stored in a refrigerator at 4°C (Park et al., 2010).

Relative humidity (RH) and temperature were monitored during sampling by using a humidity logger (Meco-920-P; Meco Instruments, India) of an accuracy of ± 3.5% for RH and ± 0.5°C for temperature.

2.1.3 Outdoor water and soil, indoor surface dust, and indoor water collection

Twenty-five outdoor water samples were collected from house wells. Twenty-one of the 25 wells were from the flooded houses which overflowed during the floods and the remaining four were from the control houses which did not overflow. Surface water from wells were collected using a sterile container that was tied with a rope. Similarly, indoor tap water samples were also collected from both flooded (n = 21) and control houses (n = 4). Samples were directly collected from the tap (after 5 min run through) in triplicates in 50 mL sterile centrifuge tubes and stored at 4°C until further analysis.

Twenty-five soil samples were collected from the front yard of all the flooded (n = 21) and non-flooded houses (n = 4). Samples were collected in sterile tubes using a clean spatula and stored at –20°C until further use (Thibeaux et al., 2017; Wójcik-Fatla et al., 2014).

Indoor surface dust samples were collected using sterile cotton swabs (n = 25) from all the flooded and control houses. Swabbing was done in the living room (25 cm × 25 cm), and the swabbing procedure was maintained consistently in all the houses. Swabs were then stored in sterile PBS solution, and the surface dust-PBS mix was transported immediately to the lab.

0.5 g of outdoor soil sample was suspended into 1 mL of water, further serially diluted 105 times. 0.1 mL of suspension was plated into the TSA and PDA media from the last dilution.

Similarly, 0.1 mL of indoor tap water and 0.1 mL of indoor surface dust-PBS mix were plated into different TSA and PDA mediums. Outdoor well water was not considered for the source attribution analysis as the tap water is sourced from the wells and was considered for source attribution analysis. All plates were incubated in similar conditions to the air samples, and colonies were differentiated based on morphology for further analysis.

2.2 Microbial Quantification

2.2.1 DNA extraction from colonies

After incubation, colonies from TSA and PDA plates were examined and picked based on the morphology. Under aseptic conditions, unique colonies were picked using the loop and suspended into 1X Saline for DNA extraction. DNA was extracted using a commercially available Purefast Bacterial/Fungal DNA extraction kit, and the extraction was followed as per the manufacturer's instruction (Helini Biomolecules® India) (Akila et al., 2018).

2.2.2 PCR analysis and sequencing

Eluted DNA was then subjected to individual PCR runs targeting the universal 16s rRNA for bacteria and ITS region for fungi. Each PCR reaction was performed in a mixture containing 25 µL of red dye master mix, 2 µL of primer mixture with forward and reverse primers of 2 pM µL1 each, 20 µL DNase-free water, and 3 µL of DNA extracted from bacterial and fungal colonies. Assays were performed using the Agilent SureCycler 8800 PCR system (Agilent Technologies, USA). The primer sequences and the respective amplification protocols were adapted from the previous study (Akila et al., 2020, 2018). Further, PCR products were subjected to Sanger Sequencing at Eurofins Genomics Pvt. Ltd., Bangalore. The sequences which contained above 95% identity values from NCBI Blast analysis were considered. The nucleotide sequences obtained in the study were given accession numbers MN12887-MN128881 for bacteria, MZ227279-MZ227350 for fungi at the NCBI GenBank. Negative control (no template control) was always maintained to monitor the crossover contamination from consumables and lab materials.

2.2.3 Endotoxin analysis

Endotoxin concentration in ambient air particulate matter was measured by Limulus Amebocyte Lysate Assay (LAL) (Chromogenic Endotoxin assay kit, Genscript, USA). All the materials used for this assay were sterilized at 180°C overnight to avoid contamination (Greisman et al., 1966). Dust particles from filter paper were extracted in endotoxin-free water with 0.05% Tween-20 solution (Douwes et al., 1995; Mueller-Anneling, 2004) and endotoxin concentration was measured per the manufacturer's instruction at 37°C (Akila et al., 2020). The concentration of endotoxin was measured by colorimetric analysis using a spectrometer at the 545 nm wavelength (Labindia analytical, India). The concentration was expressed as endotoxin units per cubic meter of air (EU m3). Endotoxin standards were prepared with LAL assay water (R2 of 0.998) (Supplementary Information, SI-Section S1).

2.2.4 Determination of chlorine and antibiotic resistance bacteria

Chlorination is the method of choice for disinfecting water bodies following flooding (U.S. EPA, 2005; WHO, 2011) (SI-Section S2). While ARBs in the outdoor environment of flooded areas have already been reported (Jaya Divakaran et al., 2019; Shankar et al., 2021), the study focused on chlorinated well water for two reasons: to evaluate the effectiveness of chlorination in eliminating pathogens and ARBs, and to determine whether ARBs are being introduced into the indoor air of households using the well water for domestic purposes.

The residual chlorine concentration from all the well water (n = 25) samples was measured using an iodometric titration assay (ISO, 1990). Since the concentration was below the detection limit, further analysis was performed to assess the chlorine resistance. All sample processing was conducted inside a class 100 vertical flow laminar hood irradiated with ultraviolet light prior to use. 0.1 mL of water sample was inoculated in TSA plates and incubated at 37°C for 2–3 days. To check the invitro chlorine resistance of bacteria, colonies were treated with calcium hypochlorite solution. Colonies selected based on morphology were separately grown in a sterile Muller-Hinton (MH) broth (Himedia Limited®) at 37°C for 24 hours. The bacterial cultures obtained were inoculated in calcium hypochlorite solutions of strengths 0.5 ppm, 1 ppm, 10 ppm, 100 ppm, 1000 ppm, 5000 ppm, and 10,000 ppm; and were allowed to remain in contact for 10, 20, and 30 min (Al-Berfkani et al., 2014). Calcium hypochlorite solutions were prepared using a 1,000,000 ppm calcium hypochlorite stock solution diluted with a sterile nutrient broth. After each incubation period of 10, 20, or 30 min, cultures were inoculated in nutrient agar and incubated at 37°C for 24 hours. The presence of bacterial growth after the incubation period was considered as a positive indication of the presence of antibiotic resistant bacteria (Al-Berfkani et al., 2014) (SI-Section S3).

These bacteria were then evaluated for their resistance to selected commonly used antibiotics. Disc diffusion method was used (Hudzicki, 2009). A single colony of each strain was inoculated in sterile MH broth and incubated for 6 hours at 37°C. A sterile swab was then used to transfer the bacterial growth onto an MH agar plate. After the plates were dry (after approximately 3 min), antibiotic discs were placed in the plates according to the Clinical & Laboratory Standards Institute (CLSI) guidelines (CLSI, 2010). Plates were inverted and incubated at 37°C for 18 hours, and the zone of inhibition was measured. Measured diameters were compared with the standard table (CLSI, 2012), and bacterial strains were categorized as resistant or sensitive (SI-Section S4).

Antibiotic resistant bacteria were characterized using Sanger Sequencing. For DNA extraction, 50 mL of water sample was centrifuged at 8000 RCF (Relative centrifugal force) for 10 min, and the pellet was immediately re-suspended with 200 µL of original water. Further DNA was extracted as per the manufacturer's instruction (QIAamp DNA extraction kit, Qiagen, Australia). The final DNA was eluted in 50 µL TE buffer and stored at –20°C until further use (Thibeaux et al., 2017). The concentration of eluted DNA was measured using a NanoDrop (Thermofisher Scientific, USA).

Eluted DNA was then subjected to individual PCR runs targeting the universal 16s region of bacteria. PCR reaction and Sanger Sequencing procedures were followed as described in Section 2.2.2. The sequences which contained above 95% identity values from NCBI Blast analysis were considered.

Due to Covid-19 restrictions, we were unable to proceed with the planned experiments to characterize the indoor air and indoor tap water for the presence of chlorine and antibiotic-resistant bacteria. Therefore, we will only compare the presence of bacterial species in the indoor air and tap water that were identified as antibiotic-resistant in the outdoor well water.

2.3 Statistical Analysis

Statistical analyses were conducted using R Studio and Microsoft Excel 2010. Logarithmic values of concentration followed a normal distribution (Shapiro-Wilk test, p > 0.05), confirming log-normal distribution (Akila et al., 2020). Multi-linear regression and Spearman rank correlation examined associations between indoor bacterial, fungal concentrations, endotoxin (dependent variables), and independent variables: meteorological factors (temperature, relative humidity), and home ecology (inhabitants, pets, flood water height, home age, room count, room size, cleaning frequency, cleaning product). Additionally, independent variables included concentrations from outdoor air, outdoor soil, indoor surface dust, and indoor tap water in flooded and non-flooded houses. Interrelationships between the variables were checked before multi-linear regression using the Durbin-Watson test.

Alpha diversity was assessed using Shannon's and Simpson's indices, capturing species richness and evenness. R Studio's vegan package computed these indices. Abundant taxa were identified by calculating relative abundance (RA) and species richness (SR) from NCBI Blast results per house (Akila et al., 2020). At the family level, we identified relatively abundant families in flooded homes compared to non-flooded ones. Student t-test assessed significant differences in microbial communities between flooded and non-flooded houses.

A clustered heat map (R Studio) compared microbial communities in indoor flooded homes with potential sources: indoor surface dust, indoor tap water, outdoor air, and outdoor soil. Principal component analysis (PCA, R Studio package) further evaluated heat map results, establishing source significance. The FEAST program, which stands for "Fast Expectation-Maximization for Microbial Source Tracking," is implemented as a Bayesian algorithm within R Studio. It estimates source contributions by employing a microbial tracking approach. Specifically, FEAST utilizes the expectation-maximization method to determine source contributions. In more detail, it treats the input microbial communities as sink and sources and then calculates the sink fractions contributed by each source. Additionally, the FEAST also reports the potential fraction of a sink attributed to different origins, collectively called an unknown source, on account of those mixing proportions which often add up to less than complete sinks (Carter et al., 2020; Shenhav et al., 2019).


3.1 Microbial Concentration in Flooded and Control Houses

Microbial concentration in indoor and outdoor air of flooded and control houses varied significantly (p < 0.05, t-test) (Fig. 2). The median concentration of bacteria and fungi present in the indoor air of flooded house was 2797 CFU m–3 and 2250 CFU m–3, respectively (Fig. 2(a)). The outdoor median bacterial and fungal concentration of flooded houses was 2250 CFU m–3 and 1708 CFU m–3, respectively (Fig. 2(b)). In contrast, the median concentration of bacteria and fungi present in the indoor air of control houses was 1010 CFU m–3 and 695 CFU m–3, respectively (Fig. 2(a)). The outdoor median bacterial and fungal concentration of control houses was 1125 CFU m–3 and 1263 CFU m–3, respectively (Fig. 2(b)).

 Fig. 2. (a) Indoor bacterial and fungal concentration of flooded and control houses. (b) Outdoor bacterial and fungal concentration of flooded and control houses.Fig. 2. (a) Indoor bacterial and fungal concentration of flooded and control houses. (b) Outdoor bacterial and fungal concentration of flooded and control houses.

In the flooded houses, bacterial concentration was higher in indoor than in outdoor air. As opposed to the commonly observed trend, the fungal concentration of flooded houses was higher in indoor than in outdoor air (Lis et al., 1997). In contrast to the flooded homes, bacterial concentration was higher in outdoor air than indoor air. In line with the previous study, fungal concentration is higher in outdoor air than the indoor air (Lis et al., 1997).

We found that observed bioaerosol concentrations in the indoor air of flooded homes were approximately three times higher than in the control houses, possibly due to variations in indoor environmental conditions. Dampness and dust resuspension due to remediation work might contribute to the elevated concentration of microbes in the flooded homes.

3.2 Bacterial Community Composition in Flooded and Control Houses

3.2.1 Indoor air

Bacteria: flooded houses

Indoor air was dominated by the phylum Proteobacteria (RA: 58%, SR: 35%), followed by Actinobacteria (RA: 23%, SR: 28%) and Firmicutes (RA:17%, SR: 34%). The remaining was contributed by Bacteroidetes (RA: 2%, SR: 3%).

Indoor air was dominated by the bacterial family Erwiniaceae (RA: 15.2%) followed by Moraxellaceae (RA: 15%). The remaining was dominated by sixteen other families. Erwiniaceae was dominated by the genus Pantoea, including P. vegans, P. agglomerans, and P. brenneri. Pantoea species are opportunistic pathogens and are frequently found in feculent material, soils, and plants (Cruz et al., 2007). Moraxellaceae family on the other hand, was dominated by the genus Acinetobacter, particularly A. calcoaceticus and A. pittii. Many species in this genus are also opportunistic pathogens that are often acquired through plumbing system (Hayward et al., 2022). The presence of these bacteria in indoor air suggests that flooding can introduce microbes from various outdoor sources to the indoor air. Additionally, flood-damaged infrastructure, such as water systems, may contribute to the indoor microbial burden.

Occurrence of these bacteria in the indoor air has implications for human health (Brady et al., 2023; Büyükcam et al., 2018). P. agglomerans (formerly known as Enterobacter agglomerans) can infect humans through penetrative trauma by vegetation (Cruz et al., 2007). Acinetobacter species are reported to cause various infections such as skin and soft tissue infections, urinary tract infections and meningitis (McConnell et al., 2013). Further, Acinetobacter species are also reported to promote the antimicrobial resistance (AMR) through horizontal and or vertical gene transfer (Hayward et al., 2022; Abe et al., 2020), increasing the risks of pathogen exposure.

Bacteria: control houses

Indoor air was dominated by the phyla Firmicutes (RA: 81%, SR: 58%) compared to other phyla. This is followed by the dominance of Proteobacteria (RA: 13%, SR: 33%) and Actinobacteria (RA: 6%, SR: 8%).

Family Bacillaceae (RA: 59%) was found dominant followed by Staphylococcaceae (RA: 21%) and the remaining was contributed by five different families. The Bacillaceae family was dominated by the genus Bacilli including dominant species B. megaterium and B. subtilis that are frequently isolated from soil, plant roots, dried food, milk and aquatic environment (Earl et al., 2008; Scholle et al., 2003; Wipat and Harwood, 1999). Soil dust carried from outside due to the wind, and human activity could be the source of indoor Bacilli (Faridi et al., 2015; Gandolfi et al., 2013; Weikl et al., 2016). Staphylococcaceae family was dominated by the species S. hominis and S. haemolyticus. Human skin harbors a wide range of microbes; staphylococci are the common genus found in the human skin (Awad, 2005; Kooken et al., 2012). Abundance of the genera Bacillus and Staphylococcus reported in this study is consistent with previous studies on indoor air (Faridi et al., 2015; Li et al., 2014; Mentese et al., 2009).

Compared to the flooded houses, indoor air of control houses was dominated by bacteria that are commonly found in the environment. Based on the literature survey, relative abundance of pathogens and opportunistic pathogens were found less in the control houses compared to the flooded houses.

3.2.2 Outdoor air

Bacteria: Flooded houses

Outdoor air was dominated by the phylum Proteobacteria (RA: 47%, SR: 38%), followed by Firmicutes (RA: 27%, SR: 34%) and Actinobacteria (RA: 25%, SR: 21%). The remaining was contributed by Bacteroidetes (RA: 1%, SR: 7%).

The most dominant families of bacterial species were, Bacillaceae (RA: 19%) followed by Pseudomonadaceae (RA: 14%). The remaining 67% was contributed by eighteen other families. The Bacillaceae family was dominated by the genus Bacilli including the species B. megaterium and B. simplex and are frequently isolated from soil, plant roots, and aquatic environment (Scholle et al., 2003; Sikorski and Nevo, 2005). Pseudomonadaceae family was dominated by the genus and Pseudomonas including the species P. stutzeri. Many species of these genera are opportunistic pathogens are frequently found in soil, plants, water, and are also associated with human microbial flora (Iglewski, 1996).

According to our findings, Bacilli and Pseudomonas were highly abundant in outdoor air of flooded homes, similar to previous findings (Lax et al., 2019). These species produce lipopeptide biosurfactants that have lytic or growth-inhibitory properties against many microorganisms (Lax et al., 2019; Raaijmakers et al., 2010), which could explain their higher abundance in outdoor air. Bacilli are known to spoil food such as bread and refrigerated foods (Remize, 2017), while Pseudomonas species spoil vegetables (Tournas, 2005). The flood damage and subsequent piling of food outside homes may have contributed to the abundance of these genera.

The Cytophagaceae family is commonly found in marine, freshwater, and terrestrial habitats (McBride et al., 2014), and was found only in the outdoor air of flooded homes, not in control homes. The presence of Enterobacteriaceae in air is an indicator of contamination from the sewage leaks (Moldoveanu, 2015). This suggests to a possible contribution of sewage to outdoor air microbial burden, consistent with the findings of the presence of fecal indicator bacteria in flood impacted outdoor soil/sediments in the region (Jaya Divakaran et al., 2019).

Bacteria: control houses

Outdoor air was dominated by the phyla Firmicutes (RA: 53%, SR: 38%) compared to other phyla. This is followed by the dominance of Proteobacteria (RA: 31%, SR: 35%) and Actinobacteria (RA: 12%, SR: 21%). The family Bacteroidetes (RA: 4%, SR: 7%) accounted for the remaining in outdoor air.

The most dominant families of bacterial species of all control houses included Bacillaceae (RA: 39%) followed by Staphylococcaceae (RA: 13%). The remaining 48% was contributed by eleven other families. Similar to the indoor air, the outdoor air was also dominated by the Bacillaceae and Staphylococcaceae family. Both the families are dominated by the genera Bacillus, Staphylococcus that are widely present in the environment.

Absence of Enterobacteriaceae family in both indoor and outdoor air of the control houses suggests that the absence of flooding prevented the introduction of these bacteria from sewage leaks into the air.

3.2.3 Alpha diversity analysis of bacteria from flooded and control houses (indoor and outdoor air)

Overall, bacterial communities in outdoor air of flooded houses were found to be more dominant (H = 2.55) than indoor air (H = 2.45). The calculated evenness of the outdoor bacterial community was high (Eh = 0.86) compared to the indoor community (Eh = 0.84), suggesting that the bacterial communities are more evenly distributed in outdoor air than indoor air. Bacterial communities in outdoor air of control houses were found to be more dominant (H = 1.94) than indoor air (H = 1.24). The calculated evenness of the outdoor bacterial community was high (Eh = 0.78) compared to the indoor community (Eh = 0.63), suggesting that the bacterial communities are more evenly distributed in outdoor air than indoor air.

Similarly, Gini-Simpson's bacterial diversity index (D) suggested diversity in the outdoor bacterial community (D = 0.90) was higher than in indoor air (D = 0.89) of flooded houses. Diversity in the outdoor bacterial community (D = 0.78) was higher than in indoor air (D = 0.59) of control houses. Overall, bacterial communities were more diverse and abundant in both indoor and outdoor air of flooded houses compared to the control houses. Open dumping of flood damaged organic materials (such as spoiled fruits, vegetables, and plant debris) were observed during the sampling, which could have helped in the proliferation of pathogenic microbes in the area (Nair, 2021).

3.3 Fungal Community Composition in Flooded and Control Houses

3.3.1 Indoor air

Fungi: flooded houses

Indoor air was dominated by the phyla Ascomycota (RA: 90%, S: 94.3%), followed by Basidiomycota (RA: 8%, SR: 4.3%), and Zygomycota (RA: 2%, SR: 1.4%).

The most dominant families of fungal species were Trichocomaceae (RA: 40%) followed by Debaryomycetaceae (RA: 14%). Twenty-one other families contributed to the remaining 46%. Trichocomaceae was dominated by the fungal genera Aspergillus and Penicillium. In line with previous study (Omebeyinje et al., 2021), our result show that indoor air of flooded houses was dominated by species of Aspergillus and Penicillium. Species of these genera are commonly found in the indoor air, however floodwaters may enrich building nutrients and create the perfect environment for fast-growing common indoor molds, mostly Aspergillus and Penicillium species (Omebeyinje et al., 2021). Debaryomycetaceae family was dominated by the genus Candida. Few species of Candida are human commensals and can overgrow in the moist environment, which can lead to skin infections (Kühbacher et al., 2017; Weng, 2015).

Though Aspergillus and Penicillium are common in molds in indoor air, the genera also consists of various opportunistic pathogens. For instance, A. niger is commonly found in indoor air and can cause coinfection through invading tissues rendered susceptible to bacterial infections (Egbuta et al., 2017). A. versicolor is also commonly found in damp environments and is reported to irritate eyes, throat, and nose as it contains more than 20 allergens (Egbuta et al., 2017). Another abundant species, Penicillium chrysogenum, is also associated with damp environments and can act as a causative agent of necrotizing esophagitis, endophthalmitis, keratitis, and asthma (Egbuta et al., 2017). Candida tropicalis and C. parapsilosis found in this study are reported to cause skin infections (Kontoyiannis et al., 2001; Mayer et al., 2013). Indoor air containing the aforementioned genera indicates a possible health risk to people living in flooded houses.

Fungi: control houses

Indoor air fungal aerosols of all control houses combined was comprised of major phyla Ascomycota (RA: 93%, SR: 92%) and Basidiomycota (RA: 7%, SR: 8%).

The most dominant families of fungal species were Trichocomaceae (RA: 58.4%) followed by Polyporaceae (RA: 7%). Nine other families contributed to the remaining composition. Trichocomaceae family was dominant in indoor air, with the genus Aspergillus, particularly the species A. niger. Polyporaceae was dominated by the genus Lenzites, specifically the species L. elegans. A. niger is a common mold found in indoor environments, soil, house dust, fruits and stored seeds (Hocking, 2006; Nadumane et al., 2016), while Lenzites species are typically found in soil, indicating that these spores are likely introduced to indoor air from outdoors. These genera were also dominant in the indoor air of flooded houses, although their concentrations were comparatively lower.

3.3.2 Outdoor air

Fungi: flooded houses

Outdoor air was dominated by the phyla Ascomycota (RA: 80%, SR: 90.3%), followed by Basidiomycota (RA: 19%, SR: 8.3%), and Zygomycota (RA: 1%, SR: 1.4%).

Outdoor fungal diversity in flood-affected houses was different than indoor fungal diversity in terms of abundance, family Trichocomaceae (RA: 49%) found dominant followed by, Polyporaceae (RA: 14%). Similar to indoor air, the Trichocomaceae family was dominated by the genera Aspergillus and Penicillium. However, A. oryzea and A. fumigatus was the dominant species of the genera Aspergillus. Polyporaceae family was dominated by the genus Trametes especially with the species T. elegans.

oryzea and A. fumigatus are commonly found in soil and in the decaying plant debris (Gomi, 2014; Latgé and Chamilos, 2019; Mousavi et al., 2016). Wet soils promote fungal growth, further water runoff could disperse the fungal spores. Plants and plant products can be colonized and infected by various Aspergillus species that produce toxic secondary metabolites such as mycotoxins in the infected tissue (Perrone et al., 2007). T. elegans, also known as Lenzites elegans, is a wood decaying fungus mostly found in hardwood forests.

The Ganodermataceae family was found only in the outdoor air. Ganoderma is the most prevalent fungal spore in the outdoor air (Hasnain et al., 2004). Both Polyporaceae and Ganodermataceae family belongs to the division Basidiomycete. It is well-known that high humidity and rain events favour basidiospores' production and proliferation in the environment (Calderón et al., 1997; Grinn-Gofroń, 2010). Chaetomium is considered a moisture indicator (Codina et al., 2008), and it was found in both indoor and outdoor air of flood-affected homes.

Fungi: control houses

Outdoor fungal aerosols were comprised of major phyla Ascomycota (RA: 64%, SR: 83%), and Basidiomycota (RA: 35%, SR: 14%). The remaining was contributed by the phylum Zygomycota (RA: 1%, SR: 3%) which was found only in the outdoor air.

Outdoor fungal diversity in control house was different than outdoor air of flooded houses in terms of abundance, with most dominant families including Trichocomaceae (RA: 45%) and Ganodermataceae (RA: 23.8%). Similar to indoor air of control houses, Trichocomaceae family was found dominant in the outdoor air as well, specifically the species A. niger. Similarly, Ganodermataceae family was dominated by the genus Ganoderma, especially the species G. tornatum. Ganoderma is a plant pathogen and frequently isolated from soil (Luangharn et al., 2021).

3.3.3. Alpha diversity analysis of fungi from flooded and control houses (indoor and outdoor air)

In contrast to bacterial communities, fungal communities of flooded houses were more dominant in indoor air (H = 2.27) than in outdoor air (H = 2.03). The calculated evenness of the indoor fungal community (Eh = 0.74) was higher than the outdoor fungal community (Eh = 0.65), suggesting that fungal communities are more evenly distributed in indoor air than in outdoor air. Gini-Simpson's diversity index also indicated that indoor fungal communities are more diverse in indoor air (D = 0.80) than in outdoor air (D = 0.73).

In contrast to the flooded house, fungal communities were more dominant in outdoor air (H = 1.60) compared to the control house's indoor air (H = 1.42). The calculated evenness of the outdoor fungal community (Eh = 0.69) was higher than the indoor fungal community (Eh = 0.65), suggesting that fungal communities are more evenly distributed in outdoor air than indoor air. Gini-Simpson's diversity index also suggested that indoor fungal communities were more diverse in outdoor air (D = 0.71) than in indoor air (D = 0.63).

Compared to the control houses, fungal communities are more diverse and abundant in both indoor and outdoor air of flooded houses. Moisture damage due to flooding and moisture damage interventions might have contributed to the growth of microbes in and around the flooded homes (Jayaprakash et al., 2017).

3.4 Possible Sources of Bacteria to the Indoor Air of Built Environment

The indoor air microbial flora was compared with the potential indoor and outdoor sources. Total bacterial concentration was used for this analysis.

Heat maps (R studio) generated with the relative abundance of bacteria indicated indoor air bacterial communities were similar to those in outdoor air and outdoor soil, followed by indoor surface dust (Fig. 3). Principal Component Analysis revealed that indoor air was positively loaded with outdoor air and outdoor soil bacterial communities (p < 0.01). Source tracking analysis using the program FEAST (Fast Expectation Maximization for microbial source tracking) confirmed the dominant contribution of outdoor air to indoor microbiome (Fig. 4); outdoor air contributed 59% and indoor dust contributed 20% of bacteria to the indoor air.

Fig. 3. (a) Heat map explaining the similarity of indoor bacterial flora with it is potential sources. (b) Similarity of indoor fungal flora with it is potential sources.Fig. 3. (a) Heat map explaining the similarity of indoor bacterial flora with it is potential sources. (b) Similarity of indoor fungal flora with it is potential sources.

 Fig. 4. Identification of potential sources of indoor bacteria and fungi using fast expectation-maximization for microbial source tracking (FEAST). Fig. 4. Identification of potential sources of indoor bacteria and fungi using fast expectation-maximization for microbial source tracking (FEAST).

Multi-linear regression analysis also showed indoor air bacterial concentration was influenced (adjusted R2 of 0.97, p < 0.01; Table 1(a)) by the significant predictor variables outdoor air bacterial concentration, indoor dust bacterial concentrations, outdoor soil bacterial concentrations, indoor relative humidity and temperature, the presence of pet animals, and the size of room. The adjusted R2 value suggests the model was able to capture a substantial portion of the variability in the observations.

Table 1(a). Results of multi-linear regressions of log10 bacterial concentration (CFU m–3) with potential predictor variables (B: Unstandardized coefficients, CI: confidence interval, SE: Standard error, β: Standardized coefficients).

Outdoor air contributes to indoor air microbial burden. Likewise, pet/domestic animals also increase the indoor microbial burden through hair shedding and movement, causing dust resuspension and the transfer of microbes (Barberán et al., 2015). The indoor air temperature and relative humidity was negatively associated with indoor bacterial concentration at p < 0.01. However, contradictory results were found by others (Brągoszewska et al., 2017; Green et al., 2003). Similarly, indoor surface dust is also negatively associated with indoor bacterial concentration at p < 0.1. The ranges of indoor relative humidity during the sampling time ranged from 71% to 91%. It has been reported that at higher relative humidity, resuspension of particles is likely to occur (Zheng et al., 2020). Room size was also negatively associated with indoor bacterial concentration at p < 0.1.

3.5 Potential Sources of Fungi to the Indoor Air of Built Environment

Heat maps (R studio) generated with the relative abundance of fungi indicated indoor air fungal communities were similar to those in indoor surface dust, followed by outdoor air and indoor tap water (Fig. 3). Source tracking analysis using the program FEAST (Fast Expectation Maximization for microbial source tracking) confirmed the dominant contribution of indoor surface dust and outdoor air to indoor microbiome (Fig. 4); outdoor air and indoor dust contributed 27% and 48%, respectively, to fungi in indoor air.

Multi-linear regression analysis showed outdoor fungal concentration, indoor surface dust, indoor tap water, indoor meteorological parameters (RH% and temperature), number and size of the room, and outdoor soil were determined as the significant predictors for the indoor fungal concentration (p < 0.01; adjusted R2 = 0.73; Table 1(b)). In line with previous studies, indoor fungal concentration was associated with outdoor sources as they primarily originate from outdoor (Brągoszewska et al., 2017; Prussin and Marr, 2015). Indoor surface dust and indoor tap water was strongly associated with indoor fungal concentration at p < 0.05. Previous study reported that 50% of indoor microbes were originated from fungi grown on indoor surface dust due to higher relative humidity (Dannemiller et al., 2017). Likewise, fungi present in the tap water could be released to indoor air through splashing and bubble breaking. In contrast to previous studies, human occupancy, presence of pets and meteorological factors were not significant for indoor fungal concentration (Dannemiller et al., 2016; Grinn-Gofroń and Bosiacka, 2015). Both bacteria and fungi favor warmer temperature and high relative humidity for growth; however, it is depending on different species (Hiwar et al., 2021). Dampness of walls vastly contributes to fungal growth by providing the source moisture; this could be the reason for positive association between indoor fungal concentration and size (p < 0.05) and number of rooms (p < 0.1).

Table 1(b). Results of multi-linear regressions of log10 fungal concentration (CFU m–3) with potential predictor variables (B: Unstandardized coefficients, CI: confidence interval, SE: Standard error, β: Standardized coefficients).


This study presents a comparative analysis of microbial concentration and composition found in both flooded and non-flooded environments. In doing so, it brings attention to the increased presence of harmful pathogens in the indoor air of flooded households, potentially leading to a higher risk of disease outbreaks after floods. Furthermore, the study identified various home ecological factors such as occupancy, the presence of pets, and room size, as well as meteorological factors like temperature and relative humidity that contribute to the indoor air's microbial burden. The research also explored potential sources of indoor microbial pollution, shedding light on the complex interplay between environmental conditions and microbial presence.

The discovery of ARB in chlorinated water raises concerns about the efficacy of chlorination as a disinfection method and the possibility of new ARB emerging. Furthermore, the presence of similar ARB species in the indoor air can make it challenging to prevent outbreaks of disease after a flood. Since antimicrobial resistance is a significant global health concern (UKHSA, 2020), the study recommends revising disinfection guidelines and innovative approaches to combat this silent pandemic.


Author Contribution

Akila Muthalagu: Experimental design, sample collection, methodology, formal analysis, writing- original draft, review and editing. Yang Lian: Analysis, review and editing. Rekha M. Ravindran: Experimental design, review and editing. Asif Qureshi: Conceptualization, experiment design, supervision, validation, resources, funding acquisition, review and editing.

Data Availability

The raw sequencing data is available based on the request from the corresponding author.

Declaration of Competing Interest

The authors declare that they have no competing interests.


This work was supported by the Research Development Fund to AQ from IIT Hyderabad.


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