Abstract

Background: Zanzibar has achieved major reductions in malaria transmission through expanded coverage of insecticide-treated net (ITNs), indoor residual spraying (IRS), strong malaria surveillance systems (epidemiological and entomological), and effective case management with Artemisinin-based Combination Therapy (ACT). However, residual transmission remains a challenge, driven by both local and imported infections that continue to threaten malaria elimination efforts. This study aimed to assess the contribution of entomological surveillance and key malaria vector control interventions, particularly ITNs and IRS, in supporting malaria elimination efforts in Zanzibar. Methods: Data on entomological surveillance, key malaria interventions and malaria epidemiological data from across elven (11) districts of Unguja and Pemba from 2015–2023 were assessed retrospectively Negative binomial regression was applied to monthly district-level counts of confirmed malaria cases to estimate the impact of interventions, using the “negbin” command in STATA and zero-inflated negative binomial (ZINB) regression model was also considered. Result: 1,188 malaria incidences were analyzed. Malaria vector density steadily increased from 2015 to 2023 with no significant correlation with malaria cases. Substantia malaria incidence differed slightly between Unguja (48.29 cases per 100,000 population) and Pemba (28.04 cases per 100,000 population), but this difference was not statistically significant (p = 0.186). In contrast incidence varied significantly across district (p < 0.001). ITNs distributions significantly associated with reductions in malaria incidence (p < 0.05), with IRRs decreasing by 50% to 99% following distribution, IRS had no statistically significant effect on malaria incidences (p = 0.806). Conclusion: Sustaining entomological surveillance and timely, targeted interventions particularly before rainy seasons and in high-risk areas—remains crucial for addressing residual transmission and advancing Zanzibar’s malaria elimination goal. However, further research should conducted to assess integration of ITNs, IRS, and behavioral interventions using modeling to predict trends and explore strategic interventions.

1. Introduction

Malaria continues to pose a significant public health challenge, despite the World Health Organization's (WHO) rigorous efforts aimed at control and elimination. Currently the key strategies employed targeting malaria vector include the large-scale distribution of insecticide-treated nets (ITNs), which have been estimated to reduce the disease burden by 68% and help stabilize transmission in some African regions ^{1, 2, 3}. On the other hand Indoor residual spraying (IRS) plays a vital role in complementing other interventions under implementation ^{4, 5, 6, 7}. Also cases management efforts using Artemisinin-based combination therapy (ACT) and effective diagnosis and treatment practices have contributed tremendously in cubing the disease ^{8, 9, 10, 11}. Furthermore, integrating ITNs and IRS with larviciding has been shown to enhance malaria transmission reduction, which aligns with WHO recommendations to include this strategy as a supplementary measure in malaria control efforts ^{9, 11, 12}.

In the United Republic of Tanzania, the entire population of the Mainland is at risk of malaria, although transmission rates differ significantly across regions. There have been a steady decline in malaria prevalence from 14.8% in 2015 to 8% in 2022 in accordance to Tanzania Demographic and Health Survey (TDHS) and Malaria Indicator Survey (MIS) ¹³.indicates Zanzibar on the other side has achieved remarkable progress in reducing malaria transmission from high-burden to near-elimination over the past two decades ¹⁴. This remarkable success has been attributed by multifaceted approaches, including the extensive use of ITNs and IRS, prompt diagnoses through malaria Rapid Diagnostic Tests (RDTs), effective treatment using ACT, and robust active surveillance systems of malaria cases ^{15, 16}. These combined strategies have enabled malaria prevalence reduction to below 1% by 2008, enabling Zanzibar to move from malaria control to elimination in 2013 ¹⁴.

These significant achievements in the diseases management have been facing the challenge of residual transmission in ensuring its sustainability. The residual transmission being fueled by local cases and imported infections, threatening Zanzibar's malaria elimination goals ^{17, 18}. Addressing this challenge necessitates a comprehensive and integrated approach that incorporates effective case management, vector control, community engagement, and entomological surveillance ¹⁹. Entomological surveillance, which involves the systematic monitoring of malaria vector populations is a crucial element of malaria control programs worldwide ²⁰. The primary aim of malaria vector surveillance is to provide essential data on mosquito population dynamics, behavior, and resistance patterns, enabling targeted and evidence-based vector control strategies that help in malaria elimination ^{21, 22, 23, 24}.

Malaria vector surveillance was established more than 10 years in Zanzibar with 11 district`s sentinel sites that was selected based in a certain criteria including malaria cases and receptivity, with the focus on monitoring vector species composition, density, behaviour and insecticide resistance to guide evidence based vector control interventions. Routine entomological activities include larval surveillance, adult collection using two household for human landing catch (HLC), two CDC light tarps, one artificial pit and five randomly selected household for pyrethrum spray catch (PSC)/prokopack aspiration. The collection/sampling was done twice a month per each sentinel sites and collected samples were processed (morphological and molecular analysis) at ZAMEP insectary in both Islands.

As Zanzibar approaches malaria elimination, there is an urgent need for targeted, cost-effective interventions to maintain progress and tackle emerging challenges. This necessity arises from community issues linked to malaria, highlighting the importance of understanding the role of entomological surveillance alongside key malaria interventions to the community for developing strategies that support sustainable elimination and prevent disease resurgence ^{10, 25}. This will be achieved by refining vector control strategies, detecting threats like insecticide resistance, and adapting to changing epidemiological patterns ²⁶, particularly concerning imported cases. While entomological surveillance has been conducted across 11 sentinel sites for over a decade, its influence on malaria elimination efforts in Zanzibar—particularly in optimizing interventions and informing decision-making was not well documented. Therefore, this study addresses this gaps by evaluating the impact of entomological surveillance and key malaria intervention from 2015 to 2023, thus providing scientific evidence that will suggest the best approaches in implementation of interventions toward achieving malaria elimination in Zanzibar.

2. Material and Methods

A retrospective research design that involves the analysis of secondary data was employed. The study involved entomological surveillance and epidemiological data from Zanzibar Malaria Elimination Program (ZAMEP) collected from January 2015 to December 2023.

Zanzibar is a semi-autonomous part of the United Republic of Tanzania consists of two main islands, Unguja and Pemba, along with several smaller islets. It lies in the Indian Ocean roughly 25–50 km off the Tanzanian mainland, between latitudes 5°40′S and 6°30′S and longitudes 39°E to 40°E. Zanzibar is divided into five regions and eleven districts (two district per each region). According to the most recent census, the population was 1,889,773 ²⁷. Zanzibar has a tropical climate featuring two rainy seasons. The “long rains” (Masika) occur between March and May and short rains (Vuli) run from October to December, and average temperatures range from 25°C to 30°C, with high humidity (more than 70% on average), especially along the coast, creating favorable conditions for mosquito breeding ^{28, 29}.

Routine entomological data were collected from ten (10) sentinel sites located per each district. From Unguja we have, Kaskazini A (Donge shehia), Kaskazini B (Bumbwini shehia), Magharibi A (Mwera shehia), Magharibi B (Kisauni shehia), Mjini (Stone Town shehia) and Kati (Cheju shehia) and Wete (Bopwe shehia), Micheweni (Tumbe Mashariki shehia), Chake Chake (Uwandani shehia) and Mkoani (Wambaa shehia) from Pemba Island (Figure 1).

Both entomological and epidemiological data were obtained from ZAMEP, the national malaria program in Zanzibar, which maintains reliable systems for collecting information on malaria prevalence, transmission and interventions. Data were sourced either from ZAMEP’s established system or from Excel files used to store information not captured in the system.

Entomological data: Routine entomological surveillance data and laboratory results from ZAMEP, stored in Excel files. Data were collected from 11sentinel sites using four methods: (1) HLC: Conducted from 06:00 pm to 06:00 am, indoors and outdoors, twice monthly per site. Two collectors worked six-hour shifts, storing mosquitoes by hour in paper cups. Samples were kept in cool boxes, before sorted and recorded the next morning at the insectary. Thoraces were preserved for sporozoite ELISA, and abdomens for PCR species identification. (2) CDC Light Traps: Two traps were used per site (one per house) from 06:00 pm to 06:00 am, (3) Prokopack/PSC: Conducted in five houses per site, collecting mosquitoes from one room where occupants had slept the previous night; and (4) Pit traps catch (PTC): Two artificial pits were established per site within 10 meters from houses and shaded with coconut leaves. Collections were between 06:30 and 08:00 am using prokopack aspirators and stored in paper cups.

Epidemiological data: Epidemiological data were extracted from ZAMEP’s Malaria Case Notification (MCN) system, a daily reporting platform used for malaria case surveillance. The system established in 2012 and expanded in 2014 to all 335 public and private health facilities in Zanzibar, captures detailed socio-demographic, epidemiological, and intervention-related information. It records both primary cases diagnosed at health facilities by microscopy or mRDTs and secondary cases identified through follow-up and Reactive Case Detection (RACD) by District Malaria Surveillance Officers (DMSOs). Variables collected include individual characteristics (address, age, sex), mRDT results, ITN use, household characteristics (household size, ITN coverage, IRS in the past 6 months), and household geo-location. For this study, monthly malaria case data from 2015 to 2023 for all districts were extracted and used to assess spatiotemporal patterns, seasonal variations, and trends in malaria cases.

ITN and IRS data: In addition to the MCN data, information from ITN mass replacement campaigns conducted in 2016, 2019, 2020 and 2023 were included in the study. IRS was initially implemented as blanket coverage across all districts twice per year. However, as malaria cases declined and transmission became more localized, the strategy shifted to focal spraying in high-incidence areas. From 2020 onward, IRS was further refined to target spraying in Unguja and targeted and reactive focal spraying in Pemba. Reports from both ITN mass distribution campaigns and IRS activities were incorporated into this study.

Population data: The population data per district obtained from census data 2022 and annual growth factor were obtained from the population per district

Data management and statistical analysis were conducted using SATA version 17 (Stata Corp LLC, College Station, Texas, USA). Both data were analyzed to identify trends, correlations, and patterns in malaria transmission, vector behavior, and intervention outcomes and negative binomial regression models used to assess the relationship between entomological indicators and malaria case trends.

Descriptive analysis: Malaria incidence was calculated by month and year, both by Island and district and expressed as cases per 100,000 populations. Population denominators, available in 2022, was calculated for previous years to 2015 adjusting for a population growth factor of 1.95% in 2015 increasing at a rate of 0.05 percentage points per year.

Statistical analysis and approaches used: The method include negative binomial regression for numbers of confirmed malaria cases monthly by district (expressed as a count variable) to estimate impact of interventions that was achieved using the “negbin” command in STATA and zero-inflated negative binomial (ZINB) regression was considered. Interventions were included in the models as dummy variables, with lagged effects assessed using 1- and 2-month lag terms. The models also accounted for potential mediation of the association between interventions and monthly malaria cases through changes in monthly mosquito density. The chi-square test and/or ANOVA was used to compare island and district malaria incidence rates.

Statistical power: The statistical significance was determined at a 95% confidence interval (CI) with a significance level of p < 0.05.

3. Results

The study analyzed 1,188 observations of malaria incidence over eight years across 11 districts to evaluate the contribution of entomological surveillance and key malaria interventions (ITN and IRS) to elimination efforts. The key results of study include: (1) although malaria vector density steadily increased from 2015 to 2023, there was no strong correlation with malaria cases; (2) malaria incidence showed differences between the two islands, Unguja and Pemba, with greater variation observed across districts; (3) ITN mass distributions were associated with significant stepwise reductions in malaria incidence (p < 0.05), with IRRs decreasing by 50% to 99% after distribution; and (4) IRS had no statistically significant effect (p = 0.806).

A total of 20,300 malaria vectors were collected across all 11 districts (Table 1), mosquito density exhibited a sustained upward trend, increasing from approximately 800 in 2025 to over 4,500 in 2023. A noticeable increase was observed in 2019, followed by continued escalation, with the most substantial rise occurring between 2022 and 2023. Yet, a small decline has seen between 2020 and 2021. Across the two island, overall vector density did not differ significantly between the islands (p = 0.075); however, it varied significantly across districts (p < 0.001) (Table 1). More importantly, the density of malaria vectors was raised across the all districts during the rainy season. However, while mosquito abundance increased overtime, the regression analysis revealed that, no strong or consistence correlation between mosquito density and malaria case counts (when fitted with regression line to show the overall trend).

The mean malaria incidence rate was higher in Unguja compared to Pemba Island. Unguja recorded a mean incidence of 48.29 cases per 100,000 population, whereas Pemba recorded a mean incidence of 28.04 cases per 100 000 population. However, this different was not statistical significant (p = 0.186).On the other hand, a marked spatial heterogeneity in malaria transmission was observed across districts of Zanzibar between 2015 and 2023, with incidence rates varying substantially among districts and demonstrating statistically significant differences in transmission intensity (p<0.001) (Figure 2).

Malaria incidence varied seasonally and temporally across Zanzibar. Compared with January, incidence rates decreased slightly in June (-1.6%, not statistically significant, p > 0.05) and sharply in October (-73.6%, statistically significant, p < 0.05). There was an observed statistically significant decline of annual malaria cases from 1,200 in 2015 to 450 in 2023 (p < 0.05). Malaria transmission peaked following the rainy season (statistically significant, p = 0.003), and substantial month-to-month variation was observed across districts (statistically significant, p < 0.05), reflecting localized factors influencing malaria transmission (Table 2).

Table 3 summarizes the impact of ITN and IRS on malaria incidence in Zanzibar between 2016 and 2023, showing that ITN campaigns were associated with significant stepwise reductions in malaria, whereas IRS implementation did not produce a statistically significant decrease. Note that IRS implementation was not uniform throughout the entire study period; it initially followed a blanket approach and later transitioned to targeted and focal implementation strategies.

4. Discussion

The study highlights four key insights into the contribution of entomological surveillance and vector control interventions to malaria elimination efforts. Despite a marked increase in malaria vector density, no corresponding rise in malaria cases was observed, consistent with evidence that transmission is influenced by factors such as vector infectivity, human behavior, and intervention coverage not only vector density ^{30, 31}. The different in incident between the Islands suggesting a comparable transmission intensity, while at district level variation highlighted substantial heterogeneity in malaria transmission, this was also observed in other studies ^{32, 33}. In contrast, ITNs demonstrated a clear positive impact on reducing malaria cases, supporting findings from previous studies ^{34, 35}. However, IRS did not show a statistically significant reduction in malaria cases, possibly due to challenges such as suboptimal coverage, insecticide resistance, and implementation variability, as reported elsewhere ^{36, 37, 38}.

This rising trend of malaria vector was influenced by good climatic drivers including favorable temperate, humidity and rainfall that provide advantageous condition for proliferation of many breeding sites that result to dramatic increases of vector density that increase the chance of malaria transmission. As other studies reveled that, rainfall and temperature as climatic drivers is significantly influence seasonal malaria transmission in Sub-Saharan Africa ^{39, 40, 41}.

There was a notable difference in malaria incidence which is influenced by multiple factors, particularly environmental conditions, climatic drivers, population density and movement as well as human behaviour particularly livelihood activities which vary across districts and contribute to differences in malaria transmission intensity within Zanzibar. Apart from that, the study found that, the variation of malaria transmission follow the rainy patterns. In other word, the transmission pattern was associated with climate variability, as similar result was documented by many studies including the study done by ⁴². Plasmodium falciparum, the predominant malaria parasite species in many sub-Saharan African countries, including Zanzibar, also was other factor as it exhibits seasonal transmission (37). Variations in malaria incidence across districts are further driven by the type and combination of interventions implemented, which are guided by malaria stratification based on transmission intensity. A modelling study by ⁴³ supports this approach, demonstrating that the choice of intervention depends on the malaria transmission strata ⁴³. Consistent with this, other studies have shown that malaria reduction is substantially greater in areas implementing multiple control interventions compared with single interventions ^{36, 44}. This means that, effective malaria control requires the implementation of multiple interventions, with particular emphasis on districts experiencing high transmission for achieving elimination goal.

ITN distribution was strongly associated with both short- and long-term reductions in malaria incidence, highlighting its central role in sustained malaria control. Evidence shows that ITNs reduce malaria transmission through physical and insecticidal protection, averting up to 68% of malaria cases ^{10, 36}, and can reduce vector populations by as much as 73% ²³. Districts with consistent ITN coverage experienced sustained declines in malaria incidence, reflecting effective disruption of transmission. This long-term impact is attributed to sustained net coverage, efficacy, improved community use, and reduced mosquito density, as supported by previous studies ^{37, 45}. Furthermore, the rotation from pyrethroid-only ITNs to PBO-ITNs during mass distribution in Zanzibar likely enhanced herd protection and further reduced malaria transmission, as recognized by WHO and supported by other studies ^{2, 14}. Overall, these findings emphasize that sustained ITN distribution, regular replacement, and community engagement that focus on behavioral adaptations that increase usage and strategies to address challenges such as insecticide resistance are critical for malaria elimination, consistent with existing evidence form other study ^{37, 46}.

Unlike ITNs, IRS did not showed statistically significant association with malaria incidence, indicating a limited or undetectable impact on transmission during the study period. This result might be affected by several externa factors including quality of IRS implementation, coverage rates, and timing of spraying as well as impact of insecticide resistance among the local mosquito species. The same factors were identified by other study ⁴⁷. Although many studies report a positive impact of IRS on reducing infection rates which is different to this study, they also note that its effectiveness varies by setting due to factors such as insecticide resistance and coverage levels ³⁸. The study done by Bhatt et al., 2016 ⁴⁸ estimated the average reduction of malaria cases by each intervention, and with ITNs was 68% while IRS was 10%, this was more similar to what happening in our study and thus, absence of a clear association may indicate that other malaria control measures, such as ITNs, played a more dominant role in reducing malaria cases, potentially masking any independent effects of IRS. This was also witnessed by other study, highlighted that, ITNs did not showed great impact in malaria reduction after removal of IRS, thus, ITNs alone did not impact the indicators of malaria transmission to the same levels as did after IRS removal ⁴⁹. This situation indicated that, the reduction of malaria infection and mosquito population was easily achieved by multiple control measures in comparison with a single method ⁴². Strengthening monitoring and evaluation mechanisms for IRS, alongside integrated vector control strategies, could provide deeper insights into its role in malaria elimination efforts.

5. Conclusion

This study examines malaria incidence and vector control effectiveness across 11 districts over eight years. Incidence is higher in Unguja than in Pemba, likely due to ecological differences, with peaks observed after the rainy season. ITN mass distribution significantly reduces malaria incidence and trends in Zanzibar, confirming its key role in control programs. In contrast, IRS shows no significant effect, possibly due to low coverage, inconsistent implementation, or misaligned timing with mosquito breeding cycles.

6. Recommendation

Given the persistent residual malaria in some districts calls for targeting high-risk areas and timely pre-rainy season interventions. Further research should be conducted to assess integration of ITNs, IRS, and behavioral interventions using modeling to predict trends and explore strategies. In-depth investigation of IRS effectiveness is also needed, considering coverage, spray quality, community adherence, insecticide resistance, and other potential confounders.

ACKNOWLEDGEMENTS

We acknowledge Ministry of health Zanzibar for the approval of analysis and publication of secondary. The authors also extend their gratitude to the management of the Zanzibar Malaria Elimination Program (ZAMEP) for providing access to the valuable data from the Malaria Case Notification (MCN) system, and other storage databases in the form of excel files which greatly contributed to this study. Finally, we sincerely appreciate the assistance of our fellow staffs for their support throughout the entire period.

Competing Interests

The authors have no competing interests.

List of Abbreviations

ACTArtemisinin-based Combination Therapy

DMSODistrict Malaria Surveillance Officer

HLCHuman Landing Catch

MCNMalaria Case Notification

TDHSTanzania Demographic and Health Survey

ZAMEPZanzibar Malaria Elimination Program

References