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Article

Combined Efficacy of Silver, Copper, and Hypochlorite Ions for Vector Control of Juvenile Aedes aegypti in Household Water Storage Containers

by
Sydney S. Turner
1,*,
James A. Smith
2,
Karin Brett
2,
Patrick I. Hancock
3,
Sophie L. Howle
2,
Victoria Cecchetti
2,
Lorin M. Bruno
2,
Julia Davis
2 and
Clay Ford
4
1
Occoquan Watershed Monitoring Laboratory, Department of Civil and Environmental Engineering, Virginia Tech, 9408 Prince William St., Manassas, VA 20110, USA
2
Department of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA 22904, USA
3
Institute on the Environment, University of Minnesota, Minneapolis, MN 55455, USA
4
Research Data Services, Shannon Library, University of Virginia, 160 McCormick Road, Charlottesville, VA 22904, USA
*
Author to whom correspondence should be addressed.
Water 2025, 17(18), 2754; https://doi.org/10.3390/w17182754
Submission received: 21 July 2025 / Revised: 21 August 2025 / Accepted: 3 September 2025 / Published: 17 September 2025
(This article belongs to the Topic Sustainable Water Purification Technologies for Multiple Applications)
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Abstract

This study evaluates the larvicidal effects of three common water disinfectants, silver (AgNO3), copper (CuSO4·5H2O), and hypochlorite (NaOCl) ions. The treatments were combined at 40–50% of their recommended drinking water guidelines and tested against late first instar and third instar Ae. aegypti larvae. The findings demonstrate that the combined application of water disinfectants yields greater efficacy in suppressing the emergence of Aedes aegypti compared to the use of the individual disinfectants alone. The silver (Ag) and copper (Cu) combination treatment (40 ppb Ag + 600 ppb Cu) showed the greatest efficacy, achieving nearly complete inhibition of emergence of the older instar larvae (98.52% [96.50, 99.47]). All treatments demonstrated high efficacy against late 1st instar Ae. aegypti larvae, with the combined copper and chlorine (Cl) treatment yielding the lowest survival rates, though individual disinfectants also produced substantial mortality. The results of this study provide critical insights to inform the design and implementation of point-of-use water treatment technologies for household water storage containers that both ensure safe drinking water and also strategically target mosquito breeding within household storage containers, thus supporting integrated vector management approaches essential for controlling neglected tropical diseases.

1. Introduction

Access to safe drinking water remains a global challenge, with over 2 billion people lacking safely managed drinking water services which contributes to an estimated 485,000 diarrheal deaths annually [1]. Simultaneously, the world faces a rising threat from vector-borne diseases (VBDs), such as dengue and Zika, affecting approximately 80% of the global population [2,3]. Mosquitoes are the most lethal disease vectors, responsible for nearly 700 million infections and over one million deaths each year [4,5]. Though transmitted through different mechanisms, both waterborne and vector-borne diseases are rooted in shared structural challenges: poor sanitation, poverty, and limited access to clean water [6,7]. In response to water insecurity, many communities rely on household water storage (HWS) [8,9], which, when improperly managed, can serve as both a breeding site for mosquitoes and a reservoir for waterborne pathogens [9,10,11,12], as illustrated in Figure 1. These overlapping vulnerabilities create an urgent need for integrated public health interventions that address water safety while simultaneously reducing vector breeding grounds, particularly in regions where household water storage is common.
According to the World Health Organization’s International Scheme to Evaluate Household Water Treatment Technologies, implementing household water treatment and safe storage (HWTS) can reduce diarrheal disease risk by up to 61% [24]. Furthermore, studies that have linked unsafe water storage practices with mosquito proliferation [6,25,26] provide plausible evidence that implementing appropriate HWTS practices can also contribute to the reduction in VBDs by reducing mosquito breeding sites. Point-of-use water treatment (POUWT) technologies provide a practical means of achieving these benefits at the household level. POUWT technologies refers to the treatment of water at the place where it is being used, commonly used for improving the quality of water for drinking and cooking purposes [24]. Since POUWT technologies and systems treat the water near the point of consumption, the risk of (re)contamination during storage and transport is reduced [27,28,29]. Design considerations for POUWT technologies are illustrated in Figure 2.
A variety of POUWT technologies exist on the market with varying degrees of effectiveness in removing various contaminants and can be selected based on the following:
  • Circumstance (e.g., local water source type, availability of replacement parts, ease of operation, cultural acceptance, and cost);
  • Standards/regulatory frameworks (e.g., World Health Organization’s Performance Criteria for Household Water Treatment Technologies [24]; National Sanitation Foundation and the American National Standards Institute standards [NSF/ANSI] [30]).
Many of these POUWT technologies treat HWS containers through the provision of an optimum dose of water disinfectants for the reduction in water pathogens originating from either the source water or conditions of storage [31,32]. Three common water disinfectants used in POUWT contexts include silver, copper, and chlorine. Chlorine is widely used because it is affordable, easy to apply, and highly effective against most waterborne pathogens, including bacteria and many viruses; however, chlorine is notably ineffective against certain protozoa, such as Cryptosporidium parvum oocysts and Mycobacteria species, and its use can result in objectionable taste and odor as well as the formation of disinfection by-products (DBPs) [29,33,34,35,36,37,38,39,40,41]. Silver has demonstrated broad biocidal activity against bacteria, viruses, and protozoa, including Cryptosporidium, and does not produce DBPs or alter water taste or odor [42,43,44,45]. Its primary drawback is the need for higher contact times to achieve inactivation [46]. Copper is effective against a wide spectrum of pathogens, such as Escherichia coli, Legionella, Salmonella, and protozoa like Cryptosporidium [47,48]. Although copper is generally less potent than silver at equivalent doses, higher allowable concentrations in drinking water standards enable its use at more practical levels. Moreover, copper tends to be significantly more affordable than silver.
Building on prior research on the larvicidal efficacy of individual water disinfectants silver, copper, and chlorine [10], this study investigates the effects of disinfectant combinations of silver (Ag), copper (Cu), and chlorine (Cl) for mosquito larval source management of Aedes (Ae.) aegypti and compares the performance of combined treatments to that of individual chemicals. The selection of silver, copper, and chlorine for this study was based on their established disinfection efficacies in water treatment processes and their common implementation in POUWT technologies and HWTS practices (Table 1 highlights some POUWT products on the global market). Thus, this study presented aims to investigate whether using these chemicals in combination can result in the inhibition of emergence of the disease vector Ae. aegypti. Our research addresses microbial safety and vector control in the same intervention, which is rarely considered in a combined framework. The findings bridge public health and vector control, thus expanding the potential application of results beyond traditional mosquito control research. To our knowledge, no prior studies have examined the simultaneous application of these three disinfectants for larval source management, representing a critical opportunity in both the vector control and household water treatment.
As there is limited research on multi-disinfectant strategies for larval control, this study seeks to address that gap. When using chemicals in tandem, there is a potential for greater disinfection efficiency while allowing for the application of lower concentrations of each chemical, resulting in reduced effects on taste and odor, minimized formation of DBPs when the disinfectants react with naturally present compounds in the water, avoidance of resistance forming by organisms/pathogens, shorter contact times, and cost savings [49,50]. Additionally, different chemical effects have been observed in the literature when water disinfectants have been used in combination. Some studies have observed synergistic effects, meaning that the interaction between two substances can produce a combined effect greater than the sum of their separate effects, for the utilization of water treatment chemicals for microbial disinfection efficiency [49,51,52,53,54].

2. Materials and Methods

This study follows protocol from previous work on the larvicidal efficacy of individual water disinfectants [10]. This study evaluates the performance of combined disinfectant treatments of silver, copper, and chlorine for the control of Ae. aegypti larvae in household water storage contexts; thus bioassay experiments were designed to simulate operational conditions relevant to point-of-use water treatment. The following sections describe the experimental procedures: culturing and rearing of Ae. aegypti in the laboratory (Section 2.1); test concentrations for treatment scenarios (Section 2.2); and evaluation of larvicidal efficacy (Section 2.3).

2.1. Culturing and Rearing

Ae. aegypti eggs were obtained from Benzon Research, Inc. (Carlisle, PA, USA). Eggs used in this study were 2–3 weeks old upon arrival. Rearing was conducted in the Water Quality Laboratory at the University of Virginia under a 12:12 h light–dark cycle. Environmental conditions were monitored using an Extech RHT20 Humidity and Temperature Datalogger (Teledyne FLIR LLC, Nashua, NH, USA). Eggs and larvae were maintained at 27.9 ± 0.2 °C (82.2 °F) in Sterlite plastic trays containing deionized (DI) water. A feeding regimen was followed using a ground larval diet composed of a 3:1 mixture of liver powder and brewer’s yeast (MP Biomedicals™, Solon, OH, USA).

2.2. Test Concentrations for Treatment Scenarios

Ae. aegypti larvae were exposed to varying concentrations of disinfectants widely used in water treatment, particularly in POUWT applications in resource-limited settings: silver ions, copper ions, and hypochlorous acid. Disinfectant concentrations were selected based on established drinking water quality guidelines (DWQGs) from the WHO and United States Environmental Protection Agency (US EPA), ensuring relevance to household water storage contexts. In the previous study [10], concentration ranges were designed relative to DWQG values for each chemical: low (~20–25%), mid (~40–50%), and high (~80–95%) of the guideline threshold (see Table 2). Testing across this range accounted for potential health, sensory, and cost considerations associated with higher disinfectant levels. Additionally, regulatory frameworks assess toxic exposures on a per-contaminant basis, with agencies such as the Agency for Toxic Substances and Disease Registry (ATSDR) and WHO evaluating silver and copper independently. Since no comprehensive studies have examined their combined effects in drinking water, caution is warranted when developing multi-metal treatments, even if each disinfectant is applied at concentrations below its individual safety threshold for human intake.
This study specifically examines combinations at the mid-range concentration level, as illustrated in Table 3, as it represents a practical balance between safety, efficacy, and affordability. Selecting mid-range levels for combinations reduces the risk of compounding toxicity or triggering taste and odor concerns that can arise at higher doses, potential issues that affect both social acceptability and long-term adoption in POUWT applications.

Preparing Stock Solutions

A 100 mMsilver stock solution was prepared with silver nitrate (AgNO3; Artcraft Chemicals, CAS No. 7761-88-8, South Glens Falls, NY, USA) in deionized (DI) water. Serial dilutions (10 mg/L → 1 mg/L → 0.1 mg/L) were then performed. Silver concentrations were verified via inductively coupled plasma mass spectrometry (ICP-MS) using an Agilent 7900 ICP-MS instrument (Agilent Technologies, Santa Clara, CA, USA) following the US EPA Method 6020B [55]. ICP-MS samples were prepared by acidifying with 2% trace metal grade nitric acid (HNO3; Fisher Chemical, Fair Lawn, NJ, USA).
A 100 mM stock solution of copper sulfate pentahydrate (CuSO4·5H2O, Alfa Aesar, Thermo Fisher Scientific, CAS No. 7758-99-8, 99% purity, Waltham, MA, USA) was prepared in deionized (DI) water. This stock was sequentially diluted to create 10 mM, 1 mM and 10 μM solutions. Copper concentrations were validated via ICP-MS following the U.S. EPA Method 6020B [55], with each sample acidified to 2% HNO3.
A sodium hypochlorite solution containing 10–15% available chlorine was obtained from Sigma-Aldrich (CAS No. 7681-52-9, St. Louis, MO, USA). This was initially diluted to prepare a 25 mg/L stock solution. From this stock, working solutions were freshly prepared immediately prior to each experimental trial. Free chlorine concentrations were quantified using the US EPA DPD Method 8021 (low-range), measured at baseline (prior to larval introduction), and subsequently at 4 and 8 h post-treatment, using a HACH DR6000 spectrophotometer.

2.3. Survival Bioassays: Evaluation of Dose Response to Water Treatment Disinfectants

For test concentrations and controls, experiments were carried out in triplicate. These trials were repeated on three separate days, each time using newly prepared test solutions and fresh batches of larvae. Larval survival and development were monitored daily under laboratory conditions. Mortality was assessed visually and by probing with a pipette tip; larvae were considered dead if they did not respond to gentle stimulation. Adult emergence were recorded to capture sub-lethal effects on larval development. These larval development outcomes were recorded for each container and analyzed statistically.

2.3.1. Experimental Setup

The laboratory procedures used in this study were adapted from the World Health Organization’s guidelines for larvicide testing in both laboratory and field settings [56] and outlined in our previous study [10]. For each test concentration, 25 mosquito larvae were introduced into 200 mL of prepared solution contained in 250 mL glass beakers, with three replicates per treatment group. Control groups, also in triplicate, consisted of larvae placed in DI water. Transfers of larvae were performed using disposable pipettes. All beakers were maintained under standardized environmental conditions previously described. Two larval age groups were tested to simulate realistic household water storage scenarios. The first scenario modeled the introduction of disinfectants into water immediately after egg deposition, with newly hatched larvae exposed to treatment. The second scenario simulated older larvae entering a disinfected household container through the use of pre-contaminated source water. To reflect these conditions, both late first instar and late third instar larvae were used in experiments. For the older instar, larval survival, and adult emergence were monitored at 24-h intervals across both treated and control groups, continuing either until all mosquitoes had emerged in control groups or until day 16 post-exposure. Trials with <80% adult emergence in control groups were deemed invalid and repeated. For younger instar, mortality of the larvae were monitored across 3 days.

2.3.2. Data Analysis

Larvicidal efficacy was evaluated following WHO guidelines [56] and methods from Ngonzi et al. [57]. Data were pooled across replicates for each treatment. When adult emergence in controls ranged between 80–95%, mortality and emergence were corrected using Abbott’s formula.
Survival (%) = 100 − ((C − T)/C × 100)
where C = percentage survival in the untreated control and T = percentage survival in the treated sample. Larvae that developed into successfully emerging adults was expressed in terms of emergence:
Emergence (%) = 100 − ((C − T)/C × 100)
where C = percentage emergence in the untreated control and T = percentage emergence in the treated sample. Inhibition of emergence (IE%) was calculated as:
IE% = 100 − (T × 100)/C
where T is emergence in the treatment and C is emergence in the control.
Statistical analyses were conducted in R (version 4.2.2, R Foundation for Statistical Computing, Vienna, Austria) using RStudio (version 2022.07.2 Build 576, RStudio, PBC, Boston, MA, USA). Descriptive statistics (mean, SD, SEM) were calculated, and probit regression was used to model the dose–response relationship between disinfectant concentration and larval survival or emergence. A mixed-effects probit model (via glmer from the lme4 package) incorporated treatment, time (as a natural spline with 2 degrees of freedom), and their interaction as fixed effects, with each experiment treated as a random effect. Pairwise comparisons were performed using the emmeans package.
For emergence inhibition modeling, day 16 control values were derived from the emergence model, and 95% confidence intervals were estimated using 100 bootstrap simulations (bootMer). Probit curves show predicted probabilities of survival or emergence over time, with 95% confidence intervals. To evaluate model fit for the larval survival data, we conducted standard diagnostics for binomial generalized linear models using the DHARMa package.
To evaluate whether the effects of chlorine, silver, and copper in combination were synergistic, additive, or antagonistic, we compared the inhibition of emergence for third instar larvae or the mortality for the first instar larvae in combined treatments against the expected mortality predicted under the assumption of independent action. Expected mortality for additive effects was calculated using Bliss independence:
EAB = EA + EB − (EA × EB)
where EA and EB represent the fractional inhibition of emergence or mortalities (proportion dead) of larvae exposed to each disinfectant individually, and EAB is the expected combined effect. If the observed mortality in the combined treatment was significantly greater than EAB, we interpreted this as potential for synergistic effects taking place. If it was not significantly different from EAB, it was considered additive. If it was lower, this suggested some potentially antagonistic effects.

3. Results and Discussion

In the following sections, we report results from tests of silver, copper, and chlorine on older juvenile Ae. aegypti (Section 3.1) and younger larvae (Section 3.2), followed by an analysis of chemical effects (Section 3.3).
It is important to note that our experiments were conducted in DI water, which provides a controlled baseline for assessing larvicidal effect. In real-world conditions, source waters often contain organic matter, suspended solids, and other constituents that exert disinfectant demand. These interactions can reduce the free concentrations of chlorine, silver, or copper through processes such as complexation with natural organic matter, precipitation with anions, adsorption to suspended solids or container surfaces, photodegradation, chlorine demand from inorganic species, and volatilization, thereby lowering efficacy.

3.1. Late Third Instar Experiments

This section presents outcomes from experiments on late 3rd instar Ae. aegypti exposed to silver and copper (Section 3.1.1), silver and chlorine (Section 3.1.2); copper and chlorine (Section 3.1.3) and copper, silver, and chlorine in combination (Section 3.1.4). Observed data results are reported as Percentage Mean ± SEM and model predictions are expressed as Predicted Probability Mean (95% Upper Confidence Interval, 95% Lower Confidence Interval).
Model diagnostics for older instars showed marginal departures from uniformity in two of the combined treatments (Cu + Ag, Ag + Cl; p ≤ 0.021). Dispersion tests also indicated slight overdispersion in the Cl-only and Ag + Cl treatments, reflecting higher variability among replicates. No evidence of zero inflation was observed in these models. These minor deviations likely reflect biological variability across larval cohorts and chlorine volatility between experimental runs.

3.1.1. Silver + Copper Exposure to Older Instar

The 40 ppb Ag + 600 ppb Cu combination treatment (Ag + Cu) observed and model predicted data for day 16 are shown in Table 4. Figure 3 illustrates their alignment, supporting the use of model predictions moving forward. The observed data for the remainder of the treatments can be found in Supplementary Information.
The Ag + Cu combo performed significantly differently from each of the chemicals separately in terms of survival (p(Ag+Cu) vs. Ag = 0.002, p(Ag+Cu) vs. Cu < 0.001) and predicting how many larva had emerged (p(Ag+Cu) vs. Ag = 0.021, p(Ag+Cu) vs. Cu < 0.001) by the end of the observational period. Additionally, the use of the chemicals together (Ag + Cu) resulted in less variability in outcome (inhibition of emergence) as illustrated in Figure 3. In the predicted survival curves illustrated in Figure 4, both copper and silver treatments initially reduced Ae. aegypti survival; however, copper effects began to plateau while silver toxicity remains relatively constant. This trend may indicate that larval susceptibility to copper diminishes with maturation, while silver maintains a sustained toxic effect throughout the developmental stages. Although we did not experimentally test mechanisms, previous work suggests several biological processes may contribute to the plateau in copper toxicity observed in older instars. For example, progressive cuticle thickening and sclerotization can reduce metal uptake across the integument [58,59] while studies in mosquitoes and aquatic invertebrates point to inducible detoxification pathways and acclimation responses that can mitigate copper stress [60,61,62].

3.1.2. Silver + Chlorine Exposure to Older Instar

The 40 ppb Ag + 1 ppm free chlorine combination treatment (Ag + Cl) model predicted survival, emergence, and inhibition of emergence data for day 16 is reported in Table 5 and Figure 5 specifically illustrates modeled survival probabilities. Analysis of the model indicates that Ag + Cl performed significantly better than either Ag or Cl separately in terms of predicted survival (p(Ag+Cl) vs. Ag = <0.001, p(Ag+Cl) vs. Cl = <0.001). For the predicted probability that a larva has emerged, the Ag + Cl treatment performed better than the chlorine alone (p(Ag+Cl) vs. Cl = 0.002), but was not significantly different from silver alone (p(Ag+Cl) vs. Ag = 0.154, by the end of the observational period. The efficacy of the 40 ppb Ag treatment, IE%model = 88.31 [78.05, 94.66], was similar to that of the Ag + Cl treatment, IE%model = 93.75 [84.65, 97.76], p(Ag+Cl) vs. Ag = 0.154).
It is important to note that chlorine is known to degrade relatively quickly in stored water, especially in the presence of organic matter and high chlorine demand, which can limit the duration of larvicidal protection. This same issue has long been a concern in household water safety programs where recontamination of containers occurs once chlorine residuals fall below protective levels [27,63,64], meaning our laboratory estimates of chlorine’s larvicidal potential may represent an upper bound of what is achievable in practice.

3.1.3. Chlorine + Copper Exposure to Older Instar

The 600 ppb Cu + 1 ppm free chlorine combination treatment (Cu + Cl) results for survival, emergence, and inhibition of emergence are shown in Table 6 for day 16. All treatments successfully decreased the larval population, resulting in the predicted probability of larval survival for 600 ppb Cu, 1 ppm Cl, and 600 ppb Cu + 1 ppm Cl was 19.87% (16.51, 24.48), 26.08% (21.84, 31.84), and 4.48% (3.19, 6.36) as compared to the predicted emergence of the controls at 93.12% (90.89, 94.90) on day 16.
Figure 6 shows the predicted probability of larval survival during the experimental timeframe. The combination treatment showed similar toxicity to copper alone during the first five days of the observational period but demonstrated greater efficacy later, as copper’s effects plateaued. This suggests that the chlorine in the combination enhanced overall toxicity, leading to increased mortality. The results of the model indicate that the Cu + Cl combo performed significantly differently from each of the chemicals separately in terms of survival (p(Cu+Cl) vs. Cu = <0.001, p(Cu+Cl) vs. Cl = <0.001) and predicting how many larva had emerged (p(Cu+Cl) vs. Cu = <0.001, p(Cu+Cl) vs. Cl = <0.001) by the end of the observational period.

3.1.4. Silver + Chlorine + Copper Exposure to Older Instar

The 40 ppb Ag + 600 ppb Cu + 1 ppm free chlorine combination treatment (Ag + Cu + Cl) predicted data for day 16 is illustrated in Figure 7. The combination of Ag + Cu + Cl demonstrated better performance compared to each chemical individually in terms of predicted survival (p(Ag+Cu+Cl) vs. Ag = 0.001, p(Ag+Cu+Cl) vs. Cu = <0.001, p(Ag+Cu+Cl) vs. Cl = <0.001) and predicting how many larva emerge (p(Ag+Cu+Cl) vs. Ag = 0.003, p(Ag+Cu+Cl) vs. Cu = 0.001, p(Ag+Cu+Cl) vs. Cl = <0.001) by the end of the observational period. The modeled IE% for treatments 40 ppb Ag, 600 ppb Cu and 1 ppm free chlorine were 89.61 [84.25, 94.24], 86.83 [81.06, 91.59], and 76.39 [69.13, 82.9], respectively. The Ag + Cu + Cl combo exhibited the highest IE% at 97.44 [94.77, 98.78] (Note: Experiments were conducted separately and do not share the same control group). The IE%, for the combined use of Ag + Cu + Cl resulted in reduced variability in outcomes/predicted outcomes comparably to the chemicals acting alone.

3.1.5. Comparing Efficacy of Water Disinfectants in Combination Exposure to Older Instar

Overall, all combination treatments demonstrated a high level of efficacy in inhibiting the emergence of the juvenile Ae. aegypti larvae and pupae into adult mosquitoes (as seen in Figure 8), and they outperformed the individual chemical treatments. All the combination models predicted viability for emergence, as the 95% confidence intervals did not ever reach 100% inhibition of emergence. When comparing combinations, the observed inhibition values had overlapping confidence intervals. Not only did the inclusion of a third disinfectant not yield a statistically distinct improvement over the dual combinations, but it was also not even the highest-performing treatment. From a practical perspective, this suggests that adding chlorine on top of silver and copper does not provide a substantial incremental benefit in larvicidal efficacy under the tested conditions. The added disinfectant simply increases cost, chemical complexity, and the potential risks of byproduct formation associated with introducing another agent. In practice, dual-agent strategies (e.g., Ag + Cu or Cu + Cl) may therefore strike the most efficient balance between efficacy and practicality.

3.2. Younger Instar Experiments

This section presents the findings of larvicidal experiments conducted on late first instar Aedes aegypti using silver nitrate, copper sulfate pentahydrate, and sodium hypochlorite treatments. The results from the observed data are expressed as Percentage Mean ± SEM, while the model predicted data are expressed as Predicted Probability Mean (95% Upper Confidence Interval, 95% Lower Confidence Interval).
Model diagnostics for younger instars indicated overall good fit. Uniformity tests did not identify significant deviations. The copper–chlorine treatment exhibited an elevated dispersion ratio (>2) and evidence of zero inflation (p = 0.008), suggesting more replicate outcomes of complete survival or complete mortality than expected under a binomial distribution. These departures are likely attributable to biological variability and the strong efficacy of some treatments.

3.2.1. Silver + Copper Exposure to Younger Instar

The model-predicted survival outcomes for younger instar Ae. aegypti larvae are summarized in Table 7 for treatments with silver nitrate (40 ppb Ag), copper sulfate (600 ppb Cu), and their combination (Ag + Cu), compared with untreated controls maintained in deionized water. The table reports predicted mean survival values and 95% confidence intervals across 24-, 48-, and 72-h exposures, corrected using Abbott’s formula (1925). After 72 h of treatment, survival rates were 22.67 ± 5.05% for 40 ppb Ag, 17.33 ± 4.29% for 600 ppb Cu, and 3.56 ± 1.18% for the Ag + Cu combination, as illustrated in Figure 9. The results of the model indicate that the Ag + Cu combo performed significantly differently from each of the chemicals separately (p(Ag+Cu) vs. Ag = <0.001, p(Ag+Cu) vs. Cu = <0.001). The difference between the Ag and Cu treatments were not significantly different (pCu vs. Ag = 0.315).

3.2.2. Silver + Chlorine Exposure to Younger Instar

The performance of silver individually in decreasing survival (40 ppb Ag: 30.22 ± 8.30%) was not as good as that of chlorine individually (1 ppm Cl: 8.44 ± 4.64%) or the combination of both chemicals together (40 ppb Ag + 1 ppm Cl: 5.78 ± 2.35%) after 72 h of exposure. Table 8 shows the predicted probability of survival data after exposure to the treatments for 24, 48, and 72 h. Figure 10 illustrates the predicted probability of survival throughout the duration of the experiment. Results of the model indicate that the Cl and Ag + Cl treatments perform better than the Ag alone treatment in terms of survival (p(Ag+Cl) vs. Ag = <0.001, pAg vs. Cl = <0.001); however, the combination treatment was not significantly different from the Cl alone treatment (p(Ag+Cl) vs. Cl = 0.446).

3.2.3. Chlorine + Copper Exposure to Younger Instar

The model predicted probability of survival data after exposure to the treatments for 24, 48, and 72 h is reported in Table 9 and Figure 11. After 72 h of exposure, all of the treatments were extremely effective in decreasing survival (600 ppb Cu: 10.67 ± 2.78%, 1 ppm Cl: 6.22 ± 4.95%, 600 ppb Cu + 1 ppm Cl: 1.33 ± 0.77%). Besides all treatments being significantly different from the controls, the only other statistical different treatments were Cu + Cl combo from the Cu alone treatment (p(Cu+Cl) vs. Cu = <0.001).

3.2.4. Comparing Efficacy of Water Disinfectants in Combination Exposure to Younger Instar

The modeled outcomes of the combined treatment are compared in Figure 12, depicting the predicted probability of survival for the various treatment combinations on day 16 of silver nitrate (40 ppb Ag), copper sulfate pentahydrate (600 ppb Cu) and sodium hypochlorite (1 ppm free chlorine). These experimental groups were not tested simultaneously and thus do not share the same controls. All treatments demonstrated a high level of efficacy in killing young Ae. aegypti larvae. Of the combinations, Cu + Cl appears to have had the most toxic effect on the younger instar larvae.
Unlike the older instar larvae experiments, the combination treatments against younger instar larvae did not always outperform the individual chemical treatments. This pattern likely reflects stage-specific physiology, i.e., underdeveloped physical barriers and detox systems. Early instar Ae. aegypti larvae possess thinner cuticles and a relatively immature peritrophic matrix/gut epithelium, which increases permeability to the disinfectants in this study [58,59]. At the same time, their detoxification capacity and energetic reserves are limited [60,65], so a potent single disinfectant can already produce near-maximal inhibition, leaving little scope for combinations to show superior efficacy. As larvae mature, barrier and detoxification mechanisms strengthen, which can alter the relative performance of single versus combined treatments.

3.3. Exploring Chemical Effects

Bliss independence analysis across both late third instar (day 16 outcomes) and late first instar (72 h mortality) assays indicated that the chemical combinations behaved additively rather than synergistically. For Ag + Cu, observed inhibition exceeded Bliss predictions slightly (<1%), consistent with additivity. Both Ag + Cl and Cu + Cl combinations showed minor underperformance relative to Bliss expectations for both the older (Ag + Cl: −2.6%; Cu + Cl: −0.72%) and younger instar larvae (Ag + Cl: −2.3%; Cu + Cl: −2.0%), but these differences were small and occurred at already high efficacy levels (>95%), meaning they are not meaningfully antagonistic. This suggests a ceiling effect because efficacy was already near complete inhibition, there was little scope left for synergy to manifest. Taken together, the combinations produced strong larvicidal effects that were largely additive, with no clear evidence of true synergism under the tested conditions.

4. Conclusions

Improperly managed household water storage containers pose a dual threat as they can harbor disease-causing pathogens and serve as breeding grounds for mosquitoes, contributing to both waterborne and vector-borne disease transmission. This study evaluated the larvicidal potential of silver ions, copper ions, and hypochlorous acid against juvenile Ae aegypti. Across both late third-instar and late first-instar Ae. aegypti larvae, all three disinfectants produced strong larvicidal effects, with combinations generally enhancing efficacy relative to single disinfectants. For older instars, dual combinations (Ag + Cu, Ag + Cl, Cu + Cl) consistently outperformed individual disinfectants, achieving inhibition of emergence above 90% and reducing variability across replicates. Adding a third agent (Ag + Cu + Cl) yielded high inhibition but did not provide clear advantages beyond dual treatments. By contrast, younger instars were highly susceptible even to single disinfectants, most notably chlorine, reflecting their less developed cuticular and detoxification defenses. In these assays, combinations provided only modest improvements, and in some cases single disinfectant exposures were nearly as effective as multi-agent treatments. All together, these results highlight stage-specific differences in that combinations offer the greatest relative benefits in older, more resistant larvae, while early instars are broadly vulnerable to single chemical exposures. Bliss independence analysis confirmed that effects were primarily additive rather than synergistic, with near-maximal efficacy at higher doses creating a ceiling effect.
While this study demonstrates the larvicidal potential of chlorine, silver, and copper individually and in combination, translating these findings into public health practice requires consideration of real-world conditions. In household and community settings, water is often stored for days, during which disinfectant concentrations decline due to decay, container interactions, and recontamination risks. Because our experiments were conducted in DI water under controlled conditions, they likely represent an upper bound of achievable efficacy. Future field studies are therefore essential, particularly across a range of source waters with varying chemistry since parameters such as pH, alkalinity, organic matter, and container material strongly influence disinfectant stability, speciation, and persistence. Monitoring these factors in parallel with larvicidal efficacy will be critical to evaluating POUWT technologies under realistic conditions and ensuring their effectiveness for both mosquito control and safe water provision.
At the same time, the existence of point-of-use products already on the market provides a foundation, and our findings may help guide both the design of new technologies and the adaptation of existing ones to specific contexts. Cost and scalability of POUWT technologies remain central determinants of household feasibility, with chlorine-based systems benefiting from established global supply chains versus silver- and copper-based technologies which are less common and thus require additional infrastructure for production and distribution. Pricing volatility, availability of raw materials, and local manufacturing capacity may also shape feasibility, meaning cost-effectiveness will vary by setting. Acceptability of disinfectants is another critical factor as we have observed how taste and odor concerns often limit chlorine uptake, while silver and copper were generally more neutral but raised concerns related to safety, environmental accumulation, and affordability. Addressing these implementation challenges alongside navigating regulatory approval will be essential to determine whether disinfectant combinations can be advanced in POUWT technologies for improving household water safety and vector control.
Ultimately, this work provides a proof-of-concept that common disinfectants when combined can serve a dual role in safeguarding drinking water quality and disrupting mosquito breeding. While this work focused on Ae. aegypti, the same principles could extend to other container-breeding vectors such as Culex and Anopheles, which also pose significant public health threats. By bridging water treatment and vector control, such integrated strategies open new pathways for holistic household water management, particularly in resource-limited settings where innovative, scalable, and acceptable solutions are most urgently needed.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17182754/s1. Figure S1. Comparing observed and model values for inhibition of emergence for silver nitrate (40 ppb Ag) and sodium hypochlorite (1 ppm free chlorine) treatments on older instar Ae. aegypti larvae on day 16. Figure S2. Comparing observed and model values for inhibition of emergence for copper sulfate (600 ppb Cu) and sodium hypochlorite (1 ppm free chlorine) treated larvae in regards to untreated larvae on day 16. Figure S3. Comparing observed and model values for inhibition of emergence for silver nitrate (40 ppb Ag), copper sulfate (600 ppb Cu) and sodium hypochlorite (1 ppm free chlorine) treated older Ae. aegypti larvae in regards to untreated larvae on day 16. Figure S4. Comparing observed and model values for survival for copper sulfate (600 ppb Cu) and silver nitrate (40 ppb Ag) treated larvae in regards to untreated larvae at 72 h. Data is corrected with Abbot’s formula (1925). Figure S5. Comparing observed and model values for survival for silver nitrate (40 ppb Ag) and sodium hypochlorite (1 ppm Cl) treated larvae in regards to untreated larvae at 72 h. Data is corrected with Abbot’s formula (1925). Figure S6. Comparing observed and model values for survival for copper sulfate (600 ppb Cu) and sodium hypochlorite (1 ppm free chlorine) treated larvae in regards to untreated larvae at 72 h. Data is corrected with Abbot’s formula (1925).

Author Contributions

Conceptualization, S.S.T. and J.A.S.; Data curation, S.S.T. and P.I.H.; Formal analysis, S.S.T., K.B., P.I.H., S.L.H., V.C., L.M.B., J.D. and C.F.; Funding acquisition, S.S.T.; Investigation, S.S.T., K.B., S.L.H., V.C., L.M.B. and J.D.; Methodology, S.S.T., J.A.S., P.I.H. and C.F.; Project administration, S.S.T.; Resources, S.S.T.; Supervision, S.S.T.; Validation, S.S.T.; Visualization, S.S.T. and P.I.H.; Writing—original draft, S.S.T.; Writing—review & editing, S.S.T. and J.A.S. All authors have read and agreed to the published version of the manuscript.

Funding

Sydney Turner received funding from the Graduate Assistance in Areas of National Need (GAAN) Program; American Association of University Women (AAUW); and the Metropolitan Washington Chapter of Achievement Rewards for College Scientists Foundation to complete her doctoral studies.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

Thank you to Jose G. Juarez for the support and guidance throughout the study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Water 17 02754 g001
Figure 1. Water insecurity stems from a combination of factors that contribute to the lack of access to safe and clean water [13,14]. Orange circles indicate the primary drivers of water insecurity. The surrounding blue circles illustrate human coping behaviors in response to this insecurity, as well as the broader implications these behaviors carry for health and well-being. Key contributors include environmental contamination [15,16], inadequate water supply infrastructure [17], climate change [18,19], conflict and political instability [20,21], and social inequity, all limiting access to reliable and safe water sources [14,22,23]. When water is perceived as scarce or unreliable, individuals and communities often adopt water storage as a coping strategy which can lead to poor public health outcomes when improperly managed [8,9].
Figure 1. Water insecurity stems from a combination of factors that contribute to the lack of access to safe and clean water [13,14]. Orange circles indicate the primary drivers of water insecurity. The surrounding blue circles illustrate human coping behaviors in response to this insecurity, as well as the broader implications these behaviors carry for health and well-being. Key contributors include environmental contamination [15,16], inadequate water supply infrastructure [17], climate change [18,19], conflict and political instability [20,21], and social inequity, all limiting access to reliable and safe water sources [14,22,23]. When water is perceived as scarce or unreliable, individuals and communities often adopt water storage as a coping strategy which can lead to poor public health outcomes when improperly managed [8,9].
Water 17 02754 g001
Water 17 02754 g002
Figure 2. Key design considerations for point-of-use water treatment (POUWT) technologies. Effective POUWT systems must balance multiple factors, including: (1) effectiveness in improving public health outcomes by reducing exposure to waterborne pathogens; (2) safety standards, ensuring disinfection agents are safe for human consumption over extended periods; (3) cost and affordability for end-users; (4) durability and long-lasting performance; (5) ease of use and access, including low maintenance, minimal energy requirements, and compatibility with locally available materials; (6) social acceptability, reflecting cultural appropriateness and societal adoption.
Figure 2. Key design considerations for point-of-use water treatment (POUWT) technologies. Effective POUWT systems must balance multiple factors, including: (1) effectiveness in improving public health outcomes by reducing exposure to waterborne pathogens; (2) safety standards, ensuring disinfection agents are safe for human consumption over extended periods; (3) cost and affordability for end-users; (4) durability and long-lasting performance; (5) ease of use and access, including low maintenance, minimal energy requirements, and compatibility with locally available materials; (6) social acceptability, reflecting cultural appropriateness and societal adoption.
Water 17 02754 g002
Water 17 02754 g003
Figure 3. Comparison of observed and model values for inhibition of emergence (IE) for Ae. aegypti larvae treated with silver ions (40 ppb Ag) and copper ions (600 ppb Cu), relative to untreated controls, on day 16. Observed values are shown with error bars representing the standard error of the mean (SEM). Modeled values are presented with 95% confidence intervals (CI), which represent the range within which the true population mean is expected to fall with 95% confidence.
Figure 3. Comparison of observed and model values for inhibition of emergence (IE) for Ae. aegypti larvae treated with silver ions (40 ppb Ag) and copper ions (600 ppb Cu), relative to untreated controls, on day 16. Observed values are shown with error bars representing the standard error of the mean (SEM). Modeled values are presented with 95% confidence intervals (CI), which represent the range within which the true population mean is expected to fall with 95% confidence.
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Water 17 02754 g004
Figure 4. Predicted probabilities of survival for older instar Ae. aegypti larvae exposed to silver ions (40 ppb Ag), copper ions (600 ppb Cu), and their combination (40 ppb Ag + 600 ppb Cu) compared to untreated controls (larvae reared in deionized water without disinfectant) on day 16. Shaded areas represent the 95% confidence interval (CI). Concentrations are expressed as parts per billion (ppb, 1 ppb = 1 µg/L).
Figure 4. Predicted probabilities of survival for older instar Ae. aegypti larvae exposed to silver ions (40 ppb Ag), copper ions (600 ppb Cu), and their combination (40 ppb Ag + 600 ppb Cu) compared to untreated controls (larvae reared in deionized water without disinfectant) on day 16. Shaded areas represent the 95% confidence interval (CI). Concentrations are expressed as parts per billion (ppb, 1 ppb = 1 µg/L).
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Figure 5. Predicted probabilities of survival of Ae. aegypti larvae exposed to silver ions (40 ppb Ag) and free chlorine (1 ppm free chlorine) compared to untreated controls (larvae reared in deionized water [DI] without disinfectant) on day 16. The shaded areas represent the 95% confidence interval (CI). Concentrations are expressed as parts per billion (ppb, 1 ppb = 1 µg/L) and parts per million (ppm, 1 ppm = 1 mg/L).
Figure 5. Predicted probabilities of survival of Ae. aegypti larvae exposed to silver ions (40 ppb Ag) and free chlorine (1 ppm free chlorine) compared to untreated controls (larvae reared in deionized water [DI] without disinfectant) on day 16. The shaded areas represent the 95% confidence interval (CI). Concentrations are expressed as parts per billion (ppb, 1 ppb = 1 µg/L) and parts per million (ppm, 1 ppm = 1 mg/L).
Water 17 02754 g005
Water 17 02754 g006
Figure 6. Predicted probabilities of survival of Ae. aegypti larvae exposed to copper ions (600 ppb Cu), free chlorine (1 ppm free chlorine), and their combination compared to untreated controls (larvae reared in deionized [DI] water without disinfectant). on day 16. The shaded areas represent the 95% confidence interval (CI). Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
Figure 6. Predicted probabilities of survival of Ae. aegypti larvae exposed to copper ions (600 ppb Cu), free chlorine (1 ppm free chlorine), and their combination compared to untreated controls (larvae reared in deionized [DI] water without disinfectant). on day 16. The shaded areas represent the 95% confidence interval (CI). Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
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Figure 7. Predicted probabilities of survival of Ae. aegypti larvae exposed to copper ions (600 ppb Cu), free chlorine (1 ppm free chlorine), and silver ions (40 ppb Ag) and their combination (Ag + Cu + Cl) compared to untreated controls (larvae reared in deionized [DI] water without disinfectant) on day 16. The shaded areas represent the 95% confidence interval. Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
Figure 7. Predicted probabilities of survival of Ae. aegypti larvae exposed to copper ions (600 ppb Cu), free chlorine (1 ppm free chlorine), and silver ions (40 ppb Ag) and their combination (Ag + Cu + Cl) compared to untreated controls (larvae reared in deionized [DI] water without disinfectant) on day 16. The shaded areas represent the 95% confidence interval. Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
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Figure 8. Comparing modeled inhibition of emergence (IE) values for combinations of silver ions (Ag, 40 ppb), copper ions (Cu, 600 ppb), free chlorine (free Cl, 1 ppm) treatments, and their combination (Ag + Cl + Cu) on older instar Ae. aegypti larvae in regard to untreated larvae on day 16. Error bars represent the 95% confidence interval. Experiments were conducted separately and do not share the same control group.
Figure 8. Comparing modeled inhibition of emergence (IE) values for combinations of silver ions (Ag, 40 ppb), copper ions (Cu, 600 ppb), free chlorine (free Cl, 1 ppm) treatments, and their combination (Ag + Cl + Cu) on older instar Ae. aegypti larvae in regard to untreated larvae on day 16. Error bars represent the 95% confidence interval. Experiments were conducted separately and do not share the same control group.
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Figure 9. Predicted probabilities of survival of Ae. aegypti larvae exposed to silver ions (40 ppb Ag), copper ions (600 ppb Cu), and their combination (Ag + Cu) compared to control larvae reared in deionized (DI) water without disinfectant at 72 h. Shaded area represents the 95% confidence intervals of the probit regression model. Concentrations are expressed as parts per billion (ppb).
Figure 9. Predicted probabilities of survival of Ae. aegypti larvae exposed to silver ions (40 ppb Ag), copper ions (600 ppb Cu), and their combination (Ag + Cu) compared to control larvae reared in deionized (DI) water without disinfectant at 72 h. Shaded area represents the 95% confidence intervals of the probit regression model. Concentrations are expressed as parts per billion (ppb).
Water 17 02754 g009
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Figure 10. Predicted probabilities of survival of Ae. aegypti larvae in contact with silver ions (40 ppb Ag), free chlorine (1 ppm free chlorine), and their combination (Ag + Cl), compared to control larvae reared in deionized (DI) water without disinfectant at 72 h. Shaded area represents the 95% confidence interval of the probit regression model. Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
Figure 10. Predicted probabilities of survival of Ae. aegypti larvae in contact with silver ions (40 ppb Ag), free chlorine (1 ppm free chlorine), and their combination (Ag + Cl), compared to control larvae reared in deionized (DI) water without disinfectant at 72 h. Shaded area represents the 95% confidence interval of the probit regression model. Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
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Figure 11. Predicted probabilities of survival of Ae. aegypti larvae in contact with copper (600 ppb Cu), free chlorine (1 ppm free chlorine), and a combination of the two disinfectants. Shaded area represents the 95% confidence interval of the probit regression model. Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
Figure 11. Predicted probabilities of survival of Ae. aegypti larvae in contact with copper (600 ppb Cu), free chlorine (1 ppm free chlorine), and a combination of the two disinfectants. Shaded area represents the 95% confidence interval of the probit regression model. Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
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Figure 12. Comparison of modeled survival (%) for late first instar Ae. aegypti larvae combinations after 72 h of exposure to combinations of silver ions (40 ppb Ag), copper ions (600 ppb Cu) and free chlorine (1 ppm free chlorine). Results are presented relative to different control groups of larvae reared in deionized water without disinfectants.
Figure 12. Comparison of modeled survival (%) for late first instar Ae. aegypti larvae combinations after 72 h of exposure to combinations of silver ions (40 ppb Ag), copper ions (600 ppb Cu) and free chlorine (1 ppm free chlorine). Results are presented relative to different control groups of larvae reared in deionized water without disinfectants.
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Table 1. Examples of point-of-use water treatment (POUWT) technologies currently in use for improving drinking water quality and safety that utilize the silver, copper, or chlorine as disinfecting agents. Product descriptions include the manufacturer, active disinfectant(s), and evaluation status according to international standards such as the World Health Organization (WHO) performance criteria or National Sanitation Foundation (NSF) certification.
Table 1. Examples of point-of-use water treatment (POUWT) technologies currently in use for improving drinking water quality and safety that utilize the silver, copper, or chlorine as disinfecting agents. Product descriptions include the manufacturer, active disinfectant(s), and evaluation status according to international standards such as the World Health Organization (WHO) performance criteria or National Sanitation Foundation (NSF) certification.
ProductManufacturerDisinfectantEvaluation
Aquatabs®
&
Aquatabs Flo		Medentech Ltd. (Wexford,
Ireland)		Chlorine in the form of sodium dichloroiso-cyanurate (NaDCC) as the active ingredientMet World Health Organization’s (WHO) performance criteria, receiving the designation of “targeted protection (bacteria and viruses only)”
H2gO PurifierAqua Research, LLC (Albuquerque, NM, USA)Electrolytic chlorine generator: splits salt (NaCl) to chlorine (Cl2) and hydrogen peroxide (H2O2)Met WHO’s performance criteria, receiving the designation of “targeted protection (bacteria and viruses only)”
H2O ResQ Copper-Silver Ion Water Storage Treatment DropsLegacy Food Storage (Salt Lake City, UT, USA)Copper–silver ion formulaNo third-party certifications (e.g., WHO or National Sanitation Foundation [NSF]) found.
MadiDrop®Silivhere Technologies Inc. (Charlottesville, VA, USA)Releases ionic silverCertified for drinking water treatment by NSF International.
Oasis Water Purification TabletsHydrachem Ltd. (Billingshurst, England)Chlorine in the
form of sodium dichloroisocyanurate (NaDCC) as the active ingredient		Met WHO’s performance criteria, receiving the designation of “targeted protection (bacteria and viruses only)”
P&G Purifier of Water PacketsProcter & Gamble (Cincinnati, OH, USA)Calcium hypochlorite (chlorine disinfectant) + ferric sulfate (coagulant/flocculant)Met WHO’s performance criteria; provides comprehensive protection by combining coagulation, flocculation, and disinfection
Table 2. Drinking water quality guidelines (DWQG) from the United States Environmental Protection Agency (US EPA) and World Health Organization (WHO) for disinfectants silver, copper, and chlorine alongside the low, medium, and high concentrations tested in larvicidal bioassays. μg/L = micrograms per liter; NTU = Nephelometric Turbidity Unit.
Table 2. Drinking water quality guidelines (DWQG) from the United States Environmental Protection Agency (US EPA) and World Health Organization (WHO) for disinfectants silver, copper, and chlorine alongside the low, medium, and high concentrations tested in larvicidal bioassays. μg/L = micrograms per liter; NTU = Nephelometric Turbidity Unit.
DisinfectantDrinking Water Quality Guideline (DWQG)Concentrations Tested (μg/L)
High
(80–95% of DWQG)		Mid
(40–50% of DWQG)		Low
(20–25% of DWQG)
Silver (Ag):US EPA and WHO: 100 μg/L204080
Copper (Cu):US EPA: 1300 μg/L
WHO: 2000 μg/L		3006001200
Free Chlorine (OCl−/HOCl):US EPA: 4000 μg/L
WHO: 2000 μg/L free chlorine dose for clear water (<10 NTU) and 4000 μg/L for turbid water (≥10 NTU) for POUWT		50010002000
Table 3. Concentrations of silver (Ag), copper (Cu), and free chlorine (Cl) tested individually and in combination in larvicidal bioassays with Ae. aegypti. Disinfectants were introduced as silver nitrate (AgNO3), copper sulfate pentahydrate (CuSO4·5H2O), and sodium hypochlorite (NaOCl). The tested concentrations included single-agent exposures (40 ppb Ag, 600 ppb Cu, or 1 ppm Cl) as well as combinations (600 ppb Cu + 40 ppb Ag; 1 ppm Cl + 40 ppb Ag; 1 ppm Cl + 600 ppb Cu). Units are expressed in parts per billion (ppb; equivalent to µg/L) for silver and copper, and parts per million (ppm; equivalent to mg/L) for chlorine.
Table 3. Concentrations of silver (Ag), copper (Cu), and free chlorine (Cl) tested individually and in combination in larvicidal bioassays with Ae. aegypti. Disinfectants were introduced as silver nitrate (AgNO3), copper sulfate pentahydrate (CuSO4·5H2O), and sodium hypochlorite (NaOCl). The tested concentrations included single-agent exposures (40 ppb Ag, 600 ppb Cu, or 1 ppm Cl) as well as combinations (600 ppb Cu + 40 ppb Ag; 1 ppm Cl + 40 ppb Ag; 1 ppm Cl + 600 ppb Cu). Units are expressed in parts per billion (ppb; equivalent to µg/L) for silver and copper, and parts per million (ppm; equivalent to mg/L) for chlorine.
Water
Disinfectants		Silver (Ag)
AgNO3		Copper (Cu)
CuSO4·5H2O		Free Chlorine (HOCl/OCl−)
NaOCl
Silver40 ppb Ag600 ppb Cu +
40 ppb Ag		1 ppm Cl +
40 ppb Ag
Copper-600 ppb Cu1 ppm Cl +
600 ppb Cu
Chlorine--1 ppm Cl
Table 4. Observed (n = 4) and modeled data for the silver (Ag, 40 ppb), copper (Cu, 600 ppb), and their combination (Ag + Cu) treatment on day 16, corrected using Abbott’s formula (1925). Observed values represent the mean, standard deviation (SD), and standard error of the mean (SEM). Modeled data are reported as predicted mean values with 95% confidence interval (CI). Outcomes include larval survival (%), adult emergence (Emerg, %), and inhibition of emergence (IE, %). Concentrations are reported in parts per billion (ppb), where 1 ppb = 1 µg/L.
Table 4. Observed (n = 4) and modeled data for the silver (Ag, 40 ppb), copper (Cu, 600 ppb), and their combination (Ag + Cu) treatment on day 16, corrected using Abbott’s formula (1925). Observed values represent the mean, standard deviation (SD), and standard error of the mean (SEM). Modeled data are reported as predicted mean values with 95% confidence interval (CI). Outcomes include larval survival (%), adult emergence (Emerg, %), and inhibition of emergence (IE, %). Concentrations are reported in parts per billion (ppb), where 1 ppb = 1 µg/L.
TreatmentAg (40 ppb)Cu (600 ppb)Ag (40 ppb) +
Cu (600 ppb)		Control
Observed
Variablemeansdsemmeansdsemmeansdsemmeansdsem
Survival (%)11.237.743.8729.1914.787.393.254.112.0691.331.720.86
Emerg (%)9.948.804.4022.0013.906.952.524.102.0588.335.032.52
IE (%)89.019.474.7474.4717.088.5497.294.382.19
Model
VariablePredicted mean [95% Confidence Interval]
Survival (%)10.00 [6.31, 14.68]29.53 [23.09, 37.71]3.53 [1.87, 5.33]92.07 [86.79, 95.58]
Emerg (%)7.15 [3.90, 1 4.09]22.47 [13.50, 33.15]1.48 [0.39, 2.94]91.81 [85.28,95.8]
IE (%)92.85 [88.24, 95.68]77.53 [68.19, 85.34]98.52 [96.50, 99.47]
Table 5. Predicted mean values with 95% confidence intervals (CI) for Ae. aegypti larvae exposed to silver ions (Ag, 40 ppb), free chlorine (Cl, 1 ppm), and their combination (Ag + Cl) relative to untreated controls reared in deionized water on day 16. Outcomes include survival (%), emergence (Emerg, %), and inhibition of emergence (IE, %). Data is corrected with Abbot’s formula (1925). Concentrations are reported as parts per billion (ppb) and parts per million (ppm).
Table 5. Predicted mean values with 95% confidence intervals (CI) for Ae. aegypti larvae exposed to silver ions (Ag, 40 ppb), free chlorine (Cl, 1 ppm), and their combination (Ag + Cl) relative to untreated controls reared in deionized water on day 16. Outcomes include survival (%), emergence (Emerg, %), and inhibition of emergence (IE, %). Data is corrected with Abbot’s formula (1925). Concentrations are reported as parts per billion (ppb) and parts per million (ppm).
TreatmentAg
(40 ppb)		Free Chlorine
(1 ppm)		Ag (40 ppb) +
Free Chlorine (1 ppm)		Control
VariablePredicted Mean [95% Confidence Interval]
Survival (%)17.30 [12.03, 23.11]29.26 [23.25, 36.70]7.38 [4.49, 11.36]94.42 [90.99, 96.72]
Emerg (%)11.69 [4.42, 24.67]31.65 [21.95, 37.68]6.25 [1.83, 15.35]94.75 [85.62, 98.53]
IE (%)88.31 [78.05, 94.66]68.35 [51.93, 82.01]93.75 [84.65, 97.76]
Table 6. Predicted mean values with 95% confidence intervals (CI) for Ae. aegypti larvae exposed to copper ions (600 ppb Cu), free chlorine (1 ppm free chlorine), and their combination (Cu + Cl) treatments on day 16. Outcomes include survival (%), emergence (Emerg, %), and inhibition of emergence (IE, %). Data is corrected with Abbot’s formula (1925).
Table 6. Predicted mean values with 95% confidence intervals (CI) for Ae. aegypti larvae exposed to copper ions (600 ppb Cu), free chlorine (1 ppm free chlorine), and their combination (Cu + Cl) treatments on day 16. Outcomes include survival (%), emergence (Emerg, %), and inhibition of emergence (IE, %). Data is corrected with Abbot’s formula (1925).
TreatmentCu
(600 ppb)		Free Chlorine
(1 ppm)		Ag (40 ppb) +
Cl (1 ppm)		Control
VariablePredicted Mean [95% Confidence Interval]
Survival (%)19.87 [16.51, 24.48]26.08 [21.84, 31.84]4.48 [3.19, 6.36]91.59 [88.75, 93.85]
Emerg (%)22.67 [19.19, 27.77]15.75 [12.87, 19.09]4.29 [2.66, 6.06]93.12 [90.89, 94.90]
IE (%)84.25 [81.08, 87.78] 77.33 [72.57, 81.12]95.71 [94.25, 97.28]
Table 7. Predicted probability of survival for younger instar Ae. aegypti larvae exposed to copper sulfate (600 ppb Cu), silver nitrate (40 ppb Ag), and their combination (Ag + Cu). Control larvae were reared in deionized (DI) water without disinfectant. Data is corrected with Abbot’s formula (1925). Values are presented as predicted means with 95% confidence intervals (CI). Concentrations are expressed as parts per billion (ppb).
Table 7. Predicted probability of survival for younger instar Ae. aegypti larvae exposed to copper sulfate (600 ppb Cu), silver nitrate (40 ppb Ag), and their combination (Ag + Cu). Control larvae were reared in deionized (DI) water without disinfectant. Data is corrected with Abbot’s formula (1925). Values are presented as predicted means with 95% confidence intervals (CI). Concentrations are expressed as parts per billion (ppb).
TreatmentAg (40 ppb)Cu (600 ppb)Ag (40 ppb) +
Cu (600 ppb)		Control
Time (h)Predicted Mean [95% Confidence Interval]
2488.50 [82.32, 92.97]84.20 [76.42, 90.07]79.73 [70.86, 86.75]97.58 [94.92, 98.96]
4853.34 [43.08, 63.37]34.49 [25.27, 44.74]13.74 [8.28, 21.25]90.60 [84.61, 94.66]
7223.28 [15.69, 32.57]17.14 [10.83, 25.41]3.33 [1.35, 7.26]82.97 [74.73, 89.25]
Table 8. Predicted probabilities of survival for younger instar Ae. aegypti larvae exposed to silver nitrate (40 ppb Ag), sodium hypochlorite (1 ppm free chlorine) and their combination (Ag + Cl). Predictions are presented as mean values with 95% confidence intervals (CI), and data were corrected using Abbott’s formula (1925).
Table 8. Predicted probabilities of survival for younger instar Ae. aegypti larvae exposed to silver nitrate (40 ppb Ag), sodium hypochlorite (1 ppm free chlorine) and their combination (Ag + Cl). Predictions are presented as mean values with 95% confidence intervals (CI), and data were corrected using Abbott’s formula (1925).
TreatmentAg (40 ppb)Cl (1 ppm)Ag (40 ppb) +
Cl (1 ppm)		Control
Time (h)Predicted Mean [95% Confidence Interval]
2483.81 [73.88, 90.89]69.37 [56.61, 80.13]64.79 [51.61, 76.40]95.17 [90.17, 97.89]
4846.51 [33.46, 59.95]21.53 [12.91, 32.80]16.64 [9.45, 26.65]84.74 [74.89, 91.61]
7230.31 [19.30, 43.48]8.99 [4.26, 16.82]6.22 [2.67, 12.68]79.17 [67.55, 87.89]
Table 9. Modeled predicted probability of survival for copper sulfate (600 ppb Cu) + sodium hypochlorite (1 ppm free chlorine) treatments for younger instar Ae. aegypti. Data is corrected with Abbot’s formula (1925). Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
Table 9. Modeled predicted probability of survival for copper sulfate (600 ppb Cu) + sodium hypochlorite (1 ppm free chlorine) treatments for younger instar Ae. aegypti. Data is corrected with Abbot’s formula (1925). Concentrations are expressed as parts per billion (ppb) and parts per million (ppm).
TreatmentCu (600 ppb)Cl (1 ppm)Cu (600 ppb) +
Cl (1 ppm)		Control
Time (h)Predicted Mean [95% Confidence Interval]
2467.88 [61.89, 73.44]68.53 [61.74, 74.74]34.71 [28.60, 41.25]94.54 [91.47, 96.67]
4823.38 [18.62, 28.75]11.32 [7.61, 16.19]3.41 [2.08, 5.36]80.37 [74.74, 85.17]
7211.83 [7.98, 16.84]6.18 [3.53, 10.18]2.44 [1.01, 5.31]75.04 [68.55, 80.73]
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MDPI and ACS Style

Turner, S.S.; Smith, J.A.; Brett, K.; Hancock, P.I.; Howle, S.L.; Cecchetti, V.; Bruno, L.M.; Davis, J.; Ford, C. Combined Efficacy of Silver, Copper, and Hypochlorite Ions for Vector Control of Juvenile Aedes aegypti in Household Water Storage Containers. Water 2025, 17, 2754. https://doi.org/10.3390/w17182754

AMA Style

Turner SS, Smith JA, Brett K, Hancock PI, Howle SL, Cecchetti V, Bruno LM, Davis J, Ford C. Combined Efficacy of Silver, Copper, and Hypochlorite Ions for Vector Control of Juvenile Aedes aegypti in Household Water Storage Containers. Water. 2025; 17(18):2754. https://doi.org/10.3390/w17182754

Chicago/Turabian Style

Turner, Sydney S., James A. Smith, Karin Brett, Patrick I. Hancock, Sophie L. Howle, Victoria Cecchetti, Lorin M. Bruno, Julia Davis, and Clay Ford. 2025. "Combined Efficacy of Silver, Copper, and Hypochlorite Ions for Vector Control of Juvenile Aedes aegypti in Household Water Storage Containers" Water 17, no. 18: 2754. https://doi.org/10.3390/w17182754

APA Style

Turner, S. S., Smith, J. A., Brett, K., Hancock, P. I., Howle, S. L., Cecchetti, V., Bruno, L. M., Davis, J., & Ford, C. (2025). Combined Efficacy of Silver, Copper, and Hypochlorite Ions for Vector Control of Juvenile Aedes aegypti in Household Water Storage Containers. Water, 17(18), 2754. https://doi.org/10.3390/w17182754

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