Literature DB >> 29147042

Insecticide-treated nets and malaria prevalence, Papua New Guinea, 2008-2014.

Manuel W Hetzel1, Justin Pulford2, Yangta Ura3, Sharon Jamea-Maiasa3, Anthony Tandrapah3, Nandao Tarongka4, Lina Lorry3, Leanne J Robinson3, Ken Lilley5, Leo Makita6, Peter M Siba3, Ivo Mueller7.   

Abstract

OBJECTIVE: To investigate changes in malaria prevalence in Papua New Guinea after the distribution of long-lasting Insecticide-treated nets, starting in 2004, and the introduction of artemisinin-based combination therapy in 2011.
METHODS: Two malaria surveys were conducted in 2010-2011 and 2013-2014. They included 77 and 92 randomly selected villages, respectively. In each village, all members of 30 randomly selected households gave blood samples and were assessed for malaria infection by light microscopy. In addition, data were obtained from a malaria survey performed in 2008-2009.
RESULTS: The prevalence of malaria below 1600 m in altitude decreased from 11.1% (95% confidence interval, CI: 8.5-14.3) in 2008-2009 to 5.1% (95% CI 3.6-7.4) in 2010-2011 and 0.9% (95% CI 0.6-1.5) in 2013-2014. Prevalence decreased with altitude. Plasmodium falciparum was more common than P. vivax overall, but not everywhere, and initially the prevalence of P. vivax infection decreased more slowly than P. falciparum infection. Malaria infections were clustered in households. In contrast to findings in 2008-2009, no significant association between net use and prevalence was found in the later two surveys. The prevalence of both fever and splenomegaly also decreased but their association with malaria infection became stronger.
CONCLUSION: Large-scale insecticide-treated net distribution was associated with an unprecedented decline in malaria prevalence throughout Papua New Guinea, including epidemic-prone highland areas. The decline was accompanied by broader health benefits, such as decreased morbidity. Better clinical management of nonmalarial fever and research into residual malaria transmission are required.

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Year:  2017        PMID: 29147042      PMCID: PMC5689189          DOI: 10.2471/BLT.16.189902

Source DB:  PubMed          Journal:  Bull World Health Organ        ISSN: 0042-9686            Impact factor:   9.408


Introduction

Historically, malaria has been endemic throughout Papua New Guinea, except in highland areas over 1600 m, where temperatures are low and there is no stable local transmission, though imported cases and epidemics do occur.– The causative parasites Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium ovale are transmitted by various Anopheles mosquito species adapted to distinct ecological niches. The epidemiology of malaria in the country and, consequently, its control are complex due to the number of parasite and mosquito species present, the variety of mosquito behaviour, the diversity of the natural environment and operational difficulties. Since 2004, the country’s national malaria control programme has been supported by the Global Fund to Fight AIDS, Tuberculosis and Malaria. National campaigns were organized to distribute free, long-lasting insecticide-treated nets at the household level and, since late 2011, malaria rapid diagnostics tests, improved diagnostic microscopy and artemisinin-based combination therapy have increasingly been provided at public and church-run health-care facilities., In 2008–2009, towards the end of the first insecticide-treated net campaign, the Papua New Guinean Institute of Medical Research conducted a country-wide malaria indicator survey. It documented that 65% of households in areas covered by the campaign owned long-lasting insecticide-treated nets and that 33% of people were using them. In addition, malaria was found to be widespread, with a heterogeneous prevalence. Light microscopy diagnosis indicated that P. falciparum was the most common species, followed by P. vivax, which dominated in several locations. A few P. malariae infections were found but P. ovale was not detected in any sample. Within 1 year of the initial insecticide-treated net campaign, a significant reduction in the prevalence, incidence and transmission of malaria was documented at selected sites, even though insect vectors tended to feed outdoors. However, entomological investigations indicated that biting patterns and changes in these patterns may reduce the impact of vector control. Subsequent national malaria surveys conducted by the Papua New Guinean Institute of Medical Research in 2010–2011 and 2013–2014 to evaluate the national malaria control programme provided evidence that coverage with long-lasting insecticide-treated nets had increased., Here, we present data on malaria prevalence from these follow-up surveys and analyse changes relative to the baseline survey of 2008–2009.

Methods

National malaria surveys were conducted from November 2010 to August 2011 and from November 2013 to August 2014. In both surveys, five villages were randomly selected from each of the country’s 20 provinces – organized in four regions – using a list of villages identified in the 2000 national census – the most up-to-date. Not all provinces or selected villages could be included because of problems with access and security. The pre-2012 province structure was adopted to ensure comparability over time: Hela Province was considered part of Southern Highlands Province and Jiwaka Province, part of Western Highlands Province. For each village, the survey team leader selected a random sample of 30 households using a list compiled by village leaders. All members of sampled households were eligible for inclusion. The sample size, which took into account financial and operational constraints, was adequate for detecting a 25% reduction in parasitaemia from 2008–2009 to 2010–2011 at the regional level at a 95% level of significance with 80% power. The first survey in 2008–2009, whose results are presented for comparison, included villages from only districts covered by the long-lasting insecticide-treated net campaign, but the method of selecting households and their members was identical to that in subsequent surveys. Data were collected using an adapted Malaria Indicator Survey questionnaire. Household heads provided details of each household member’s demographic characteristics and coverage by malaria interventions. A capillary blood sample was collected by finger-stick from each available, consenting household member aged over 5 months. Trained study nurses prepared one thick and one thin blood film for light microscopy. The haemoglobin concentration was measured using a portable HemoCue Hb 201+ photometric analyser (HemoCue AB, Ängelholm, Sweden). Symptomatic household members were offered a malaria rapid diagnostic test and treatment or referral to the nearest health-care facility, where appropriate. Axillary temperature was measured using an electronic thermometer and children aged between 2 and 9 years had their spleen palpated. Each patient’s blood sample was accompanied by information on recent travel. The locations of the survey villages were determined using a hand-held Garmin eTrex Global Positioning System device (Garmin Ltd., Olathe, United States of America). Malaria was diagnosed by light microscopy at the Papua New Guinean Institute of Medical Research following established procedures., Each slide was examined independently by two microscopists, each viewing a minimum of 200 thick film fields. Slides with discordant results were examined by a third microscopist, who was certified at World Health Organization (WHO) level 1 or 2. A slide was considered positive for malaria if judged positive by at least two microscopists. For the 2010–2011 survey, additional assessments of unclear species identifications were performed at the Australian Army Malaria Institute in Australia by WHO-certified level-1 malaria microscopists. The number of parasites per 200 white blood cells was determined. The study was approved by the Papua New Guinea Medical Research Advisory Committee (MRAC no. 07.30 and no. 10.12).

Data analysis

Measures of the prevalence of malaria infection and morbidity were age-standardized using the standard population for Asia given by the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH). Results are presented separately for villages below 1600 m in altitude and include comparisons with data from the 2008–2009 survey. For villages at 1600 m or higher, we compared data from the 2010–2011 and 2013–2014 surveys only as the 2008–2009 survey included few highland villages. To account for stratified sampling, national estimates were weighted, as described elsewhere. Splenomegaly was defined as a palpable spleen (i.e. Hackett grade 1 to 5) and anaemia was defined according to WHO recommendations, which include age-specific cut-offs and altitude corrections. Living in a high-quality house served as a proxy for having both good sanitation and a relatively high socioeconomic status, as defined elsewhere. Binary variables were compared using χ tests and logistic regression, and non-normally distributed variables were compared using the non-parametric Mann–Whitney U test. Data analyses were conducted using Stata/IC v. 14.0 (StataCorp LP., College Station, USA) and the survey design was taken into account by using Statas set of commands for survey data analysis (svy).

Results

In the 2010–2011 survey, blood samples were collected from 10 060 individuals. Of the 77 villages included, 58 (75.3%) were below 1200 m in altitude, 5 (6.5%) were between 1200 and 1599 m and 14 (18.2%), with 1539 participants, were at 1600 m or higher (Table 1). In the 2013–2014 survey, blood samples were collected from 8408 individuals. Of the 92 villages included, 66 (71.7%) were below 1200 m, 4 (4.3%) were between 1200 and 1599 m and 22 (23.9%), with 1536 participants, were at 1600 m or higher (Table 1). The small number of villages at intermediate altitudes reflects the population distribution in Papua New Guinea. The age distribution of survey participants is shown in Table 2. In the 2010–2011 survey, the participants’ median age was 19 years (interquartile range, IQR: 8–36): 14.1% (1418/10 060) were aged under 5 years and 52.8% (5290/10 028) were female. In the 2013–2014 survey, the comparable figures were 22 years (IQR: 9–38), 11.7% (985/8408) and 52.3% (4363/8348), respectively.
Table 1

National malaria surveys, Papua New Guinea, 2010–2014

Region and province2010–2011 survey
2013–2014 survey
Villagesa
Individuals tested
Villagesa
Individuals tested
No. (%)No. (%)No. (%)No. (%)
Total77 (100)10 060 (100)92 (100)8408 (100)
Southern Region
01. Western3 (3.9)376 (3.7)5 (5.4)504 (6.0)
02. Gulf4 (5.2)577 (5.7)4 (4.3)504 (6.0)
03. Central5 (6.5)814 (8.1)5 (5.4)474 (5.6)
04. National Capital District5 (6.5)673 (6.7)4 (4.3)301 (3.6)
05. Milne Bay5 (6.5)721 (7.2)4 (4.3)324 (3.9)
06. Oro5 (6.5)740 (7.4)5 (5.4)631 (7.5)
Total27 (35.1)3 901 (38.8)27 (29.3)2738 (32.6)
Highlands Region
07. Southern Highlands
    Altitude ≥ 1600 m4 (5.2)494 (4.9)4 (4.3)335 (4.0)
08. Enga
    Altitude ≥ 1600 m5 (6.5)498 (5.0)6 (6.5)335 (4.0)
09. Western Highlands
    Altitude < 1600 m3 (3.9)295 (2.9)2 (2.2)164 (2.0)
    Altitude ≥ 1600 m2 (2.6)188 (1.9)3 (3.3)213 (2.5)
10. Chimbu
    Altitude < 1600 m1 (1.3)140 (1.4)1 (1.1)85 (1.0)
    Altitude ≥ 1600 m3 (3.9)359 (3.6)4 (4.3)253 (3.0)
11. Eastern Highlands
    Altitude < 1600 mNDND2 (2.2)171 (2.0)
    Altitude ≥ 1600 mNDND3 (3.3)258 (3.1)
Total18 (23.4)1 974 (19.6)25 (27.2)1814 (21.6)
Momase Region
12. Morobe
    Altitude < 1600 m5 (6.5)672 (6.7)3 (3.3)282 (3.4)
    Altitude ≥ 1600 m0 (0)0 (0)2 (2.2)142 (1.7)
13. Madang4 (5.2)479 (4.8)5 (5.4)447 (5.3)
14. East Sepik5 (6.5)665 (6.6)6 (6.5)461 (5.5)
15. Sandaun3 (3.9)403 (4.0)4 (4.3)645 (7.7)
Total17 (22.1)2 219 (22.1)20 (21.7)1977 (23.5)
Islands Region
16. Manus5 (6.5)629 (6.3)5 (5.4)547 (6.5)
17. New Ireland5 (6.5)708 (7.0)5 (5.4)494 (5.9)
18. East New Britain5 (6.5)629 (6.3)5 (5.4)409 (4.9)
19. West New BritainNDNDNDND
20. BougainvilleNDND5 (5.4)429 (5.1)
Total15 (19.5)1 966 (19.5)20 (21.7)1879 (22.3)

ND: not determined.

a For security and operational reasons, 23 villages could not be surveyed in 2010 to 2011 and 10 could not be surveyed in 2013 to 2014.

Table 2

Age of participants, national malaria surveys, Papua New Guinea, 2010–2014

Age, years 2010–2011 survey
2013–2014 survey
No. (%)No. (%)
< 172 (0.7)95 (1.1)
1–41346 (13.4)890 (10.6)
5–91621 (16.1)1218 (14.5)
10–141137 (11.3)944 (11.2)
15–19888 (8.8)728 (8.7)
20–392885 (28.7)2510 (29.9)
≥ 402080 (20.7)1967 (23.4)
Missing values31 (0.3)56 (0.7)
Total10060 (100)8408 (100)
ND: not determined. a For security and operational reasons, 23 villages could not be surveyed in 2010 to 2011 and 10 could not be surveyed in 2013 to 2014.

Malaria prevalence

Nationally, in villages below 1600 m in altitude, the age-standardized prevalence of malaria, as diagnosed by light microscopy, decreased significantly from 11.1% (95% confidence interval, CI: 8.5–14.3) in 2008–2009 to 5.1% (95% CI: 3.6–7.4) in 2010–2011 (P < 0.001) and to 0.9% (95% CI: 0.6–1.5) in 2013–2014 (P < 0.001). The prevalence of P. falciparum infection was higher than that of P. vivax infection in all surveys (Table 3). There was no evidence of P. ovale in any sample. For individual Plasmodium species, the difference in infection prevalence between subsequent surveys was significant at a P-value ≤ 0.001 for all comparisons except for P. malariae infection, for which the P-value for the difference between subsequent surveys was < 0.05, and for mixed P. falciparum and P. vivax infection between the 2008–2009 and 2010–2011 surveys, where the decrease was not significant.
Table 3

Age-standardized prevalence of Plasmodium infection below 1600m, by species, national malaria surveys, Papua New Guinea, 2008–2014

Plasmodium speciesInfection prevalence % (95% CI)
2008–2009 surveya2010–2011 survey2013–2014 survey
(n = 6424)b(n = 8521)b(n = 6872)b
All species11.1 (8.5–14.3)5.1 (3.6–7.4)0.9 (0.6–1.5)
P. falciparum6.6 (4.9–8.8)3.0 (1.9–4.6)0.8 (0.5–1.2)
P. vivax3.1 (1.9–4.9)2.0 (1.4–2.9)0.1 (0.0–0.3)
P. malariae0.3 (0.1–0.6)0.1 (0.0–0.2)0
P. falciparum and P. vivax0.3 (0.1–0.5)0.2 (0.1–0.4)0.01 (0.0–0.08)

CI: confidence interval; P. falciparum: Plasmodium falciparum; P. malariae: Plasmodium malariae; P. vivax: Plasmodium vivax.

a Data from the 2008–2009 survey were re-analysed by applying age-standardization.

b The number of survey participants living in villages below 1600 m in altitude.

CI: confidence interval; P. falciparum: Plasmodium falciparum; P. malariae: Plasmodium malariae; P. vivax: Plasmodium vivax. a Data from the 2008–2009 survey were re-analysed by applying age-standardization. b The number of survey participants living in villages below 1600 m in altitude. Between the 2008–2009 and 2010–2011 surveys, an increase in the prevalence of P. vivax infection was noted in two of the country’s four regions (Fig. 1) and in several provinces (Fig. 2 and Fig. 3), which led to a decrease in the ratio of P. falciparum to P. vivax infection. However, the prevalence of infection by both species decreased in all provinces between 2010–2011 and 2013–2014. In 2013–2014, no parasites were detected in any sample from 11 of the 19 provinces surveyed (Table 4; available at: http://www.who.int/bulletin/volumes/94/10/16-189902).
Fig. 1

Age-standardized prevalence of Plasmodium infection and insecticide-treated net use, by region and survey date, national malaria surveys, Papua New Guinea, 2008–2014

Fig 2

Age-standardized prevalence of Plasmodium infection and insecticide-treated net use in lower-prevalence areas, by province and survey date, national malaria surveys, Papua New Guinea, 2008–2014

Fig 3

Age-standardized prevalence of

Table 4

Age-standardized prevalence of Plasmodium infection, by province, national malaria surveys, Papua New Guinea, 2010–2014

Province and region2010–2011 survey
2013–2014 survey
No. of participantsNeta use (%)Infection prevalence (%)
No. of participantsNeta use (%)Infection prevalence (%)
All Plasmodium speciesP. falciparumP. vivaxAll Plasmodium speciesP. falciparumP. vivax
Southern Region
01. Western37683.91.10.90.250473.10.00.00.0
02. Gulf57780.60.80.80.050480.00.00.00.0
03. Central81475.25.62.43.247462.60.00.00.0
04. National Capital District67315.70.60.20.230120.70.00.00.0
05. Milne Bay72173.58.32.94.232463.50.90.00.9
06. Oro74065.52.21.60.663162.50.00.00.0
Total390160.03.31.51.5273859.80.10.00.1
Highlands Region
07. Southern Highlands
   Altitude ≥ 1600 m49450.51.00.70.333528.90.40.40.0
08. Enga
   Altitude ≥ 1600 m49831.20.80.80.03357.40.00.00.0
09. Western Highlands
   Altitude < 1600 m29532.30.50.50.016447.90.00.00.0
   Altitude ≥ 1600 m18829.50.00.00.021342.20.00.00.0
10. Chimbu
   Altitude < 1600 m14041.80.00.00.08529.90.00.00.0
   Altitude ≥ 1600 m35933.50.50.50.025353.10.00.00.0
11. Eastern Highlands
   Altitude < 1600 mNDNDNDNDND17138.00.00.00.0
   Altitude ≥ 1600 mNDNDNDNDND25838.40.00.00.0
Total 197436.20.60.50.1181432.90.10.10.0
Momase Region
12. Morobe
   Altitude < 1600 m67245.74.83.61.228277.30.30.30.0
   Altitude ≥ 1600 m0NANANANA14255.00.00.00.0
13. Madang47945.76.34.51.844770.33.33.30.0
14. East Sepik66561.93.92.11.746183.10.00.00.0
15. Sandaun40330.111.05.04.964552.83.02.40.5
Total221947.05.93.62.1197767.71.91.60.2
Islands Region
16. Manus62932.01.80.71.354756.50.10.10.0
17. New Ireland70828.412.97.95.849462.32.92.30.4
18. East New Britain62950.89.25.43.640951.64.33.01.0
19. West New BritainNDNDNDNDNDNDNDNDNDND
20. BougainvilleNDNDNDNDND42955.60.00.00.0
Total 196636.88.34.93.7187956.51.71.20.3

NA: not applicable; ND: not determined; P. falciparum: Plasmodium falciparum; P. vivax: Plasmodium vivax.

a Long-lasting insecticide-treated nets.

Age-standardized prevalence of Plasmodium infection and insecticide-treated net use, by region and survey date, national malaria surveys, Papua New Guinea, 2008–2014 P. falciparum: Plasmodium falciparum; P. vivax: Plasmodium vivax. Note: Error bars represent 95% confidence intervals. Age-standardized prevalence of Plasmodium infection and insecticide-treated net use in lower-prevalence areas, by province and survey date, national malaria surveys, Papua New Guinea, 2008–2014 P. falciparum: Plasmodium falciparum; P. vivax: Plasmodium vivax. Age-standardized prevalence of P. falciparum: Plasmodium falciparum; P. vivax: Plasmodium vivax. NA: not applicable; ND: not determined; P. falciparum: Plasmodium falciparum; P. vivax: Plasmodium vivax. a Long-lasting insecticide-treated nets. In highland villages at 1600 m and above, the age-standardized prevalence of malaria decreased from 0.7% (95% CI: 0.3–1.2) in 2010–2011 to 0.1% (95% CI: 0–0.7) in 2013–2014 (P = 0.004). In the 2010–2011 survey, the prevalence of P. falciparum infection was higher than that of P. vivax infection in highland villages: 0.6% (95% CI: 0.3–1.1) and 0.1% (95% CI: 0–0.7), respectively. In the 2013–2014 survey, the prevalence of P. falciparum infection was 0.1% (95% CI: 0–0.4), whereas no P. vivax infections were detected. Moreover, no P. malariae, P. ovale or mixed infections were found.

Predictors of infection

Regression analysis findings are presented in Table 5. Univariable logistic regression found that, in 2010–2011, malaria infection was significantly less likely above 1600 m (odds ratio, OR: 0.15; 95% CI: 0.06–0.38); in 2013–2014, the corresponding OR was  0.04 (95% CI: 0.00–0.33). The prevalence of infection below 1600 m was significantly lower in older individuals in all years (Fig. 4): P < 0.001 for the 2008–2009 and 2010–2011 surveys and P = 0.03 for the 2013–2014 survey. For P. falciparum infection, the peak prevalence shifted to a younger age between 2008–2009 and 2010–2011, but there was no corresponding change for P. vivax infection (Fig. 5). In 2013–2014, the difference in the prevalence of P. falciparum and P. vivax infection between age groups was not significant. However, 62.7% (95% CI: 42.2–79.4) of P. vivax infections and 9.1% (95% CI: 3.4–22.0) of P. falciparum infections occurred in children aged under 5 years.
Table 5

Factors associated with malaria infection, national malaria surveys, Papua New Guinea, 2010–2014

Risk factorRisk of malaria infection
Univariable logistic regression analysis
Multivariable logistic regression analysis
OR (95% CI)aOR (95% CI)
2010–2011 survey
Village at 1600 m or higher0.15 (0.06–0.38)0.16 (0.06–0.42)
Age < 5 years2.98 (2.40–3.71)2.59 (2.08–3.23)
Long-lasting insecticide-treated net use1.38 (1.00–1.90)1.09 (0.82–1.45)
High-quality housea0.30 (0.11–0.83)0.25 (0.08–0.79)
Percentage net use in village1.01 (1.00–1.02)ND
2013–2014 survey
Village at 1600 m or higher0.04 (0.00–0.33)0.04 (0.00–0.36)
Age < 5 years1.59 (0.74–3.44)1.47 (0.68–3.21)
Long-lasting insecticide-treated net use1.42 (0.83–2.45)1.08 (0.64–1.82)
High-quality housea1.00ND
Percentage net use in village1.01 (1.00–1.03)ND

aOR: adjusted odds ratio; CI: confidence interval; ND: not determined; OR: odds ratio.

a Living in a high-quality house served as a proxy for having both good sanitation and a relatively high socioeconomic status.

Fig. 4

Prevalence of Plasmodium infection below 1600 m, by age and survey date, national malaria surveys, Papua New Guinea, 2008–2014

Fig. 5

Prevalence of P. falciparum and P. vivax infection below 1600 m, by age and survey date, national malaria surveys, Papua New Guinea, 2008–2014

aOR: adjusted odds ratio; CI: confidence interval; ND: not determined; OR: odds ratio. a Living in a high-quality house served as a proxy for having both good sanitation and a relatively high socioeconomic status. Prevalence of Plasmodium infection below 1600 m, by age and survey date, national malaria surveys, Papua New Guinea, 2008–2014 Note: The study age groups, as indicated in the figure, were 0–0.9, 1.0–4.9, 5.0–9.9, 10.0–14.9, 15.0–19.9, 20.0–39.9 and ≥40 years. Prevalence of P. falciparum and P. vivax infection below 1600 m, by age and survey date, national malaria surveys, Papua New Guinea, 2008–2014 P. falciparum: Plasmodium falciparum; P. vivax: Plasmodium vivax. Note: The study age groups, as indicated in the figures, were 0–0.9, 1.0–4.9, 5.0–9.9, 10.0–14.9, 15.0–19.9, 20.0–39.9 and ≥40 years. Long-lasting insecticide-treated nets were used by 32.5% (95% CI: 27.0–38.4) of the population nationally in 2008–2009, by 48.3% (95% CI: 41.8–54.9) in 2010–2011 and by 53.9% (95% CI: 49.4–58.4) in 2013–2014. In the 2008–2009 survey, a significant association was found between net use and a lower risk of malaria infection (adjusted odds ratio, aOR: 0.64; 95% CI: 0.54–0.76). However, no corresponding association was found in the 2010–2011 survey (aOR: 1.09; 95% CI: 0.82–1.45), in an analysis that adjusted for altitude, age and housing quality, or in the 2013–2014 survey (aOR: 1.08; 95% CI: 0.64–1.82), in an analysis that adjusted for altitude and age (Table 5). In 2010–2011, people living in high-quality houses were significantly less likely to be infected (aOR: 0.25; 95% CI: 0.08–0.79). Malaria cases were clustered in households. Univariable analysis found that, in 2010–2011, the odds of infection were over 26 times higher for individuals living with an infected person than for those who were not (OR: 25.65; 95% CI: 16.18–40.67); in 2013–2014, the odds were over 77 times higher (OR: 77.16; 95% CI: 41.61–143.09). In 2010–2011, 47% of malaria-infected individuals lived in a household with another infected person; in 2013–2014, the corresponding proportion was 25%.

Morbidity

In all surveys, individuals infected with malaria were significantly more likely than those without to report a recent fever episode, to show symptoms of acute fever (i.e. an axillary temperature over 37.5 °C), to be anaemic or, in those aged 2 to 9 years, to have splenomegaly (P < 0.01 for all). Although the proportion of the population with a recent history of fever decreased over time (Fig. 6), the association between malaria infection and a recent history of fever became stronger, particularly after 2010: the OR adjusted for age was 2.05 (95% CI: 1.41–2.99) in 2008–2009, 2.57 (95% CI: 1.74–3.81) in 2010–2011 and 12.34 (95% CI: 4.56–33.33) in 2013–2014. In 2013–2014, 37.4% of all infected individuals reported a recent fever episode (Fig. 6) and 3.7% had an acute fever (Fig. 7). The prevalence of splenomegaly in participants aged 2 to 9 years also decreased over time (Fig. 8) and again the association with infection tended to become stronger: the OR adjusted for age was 4.72 (95% CI: 2.38–9.34) in 2008–2009, 10.0 (95% CI: 5.10–19.60) in 2010–2011 and 21.84 (95% CI: 5.52–88.46) in 2013–2014. The prevalence of anaemia remained high over time and increased between 2010–2011 and 2013–2014 (Fig. 9 and Fig. 10). Independent of the effect of malaria infection, in 2013–2014, anaemia was significantly associated with residing in a village below 1200 m in altitude (aOR: 8.63; 95% CI: 6.66–11.18), age under 5 years (aOR: 4.38; 95% CI: 2.96–6.46) and female sex (aOR: 1.54; 95% CI: 1.35–1.75).
Fig. 6

Participants with a history of fever in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014

Fig. 7

Participants with acute fever in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014

Fig. 8

Participants aged 2 to 9 years with splenomegaly in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014

Fig. 9

Participants with anaemia in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014

Fig. 10

Participants with severe anaemia in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014

Participants with a history of fever in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014 Notes: The black line shows the proportion for each whole survey population. Differences between subsequent years in the proportion of the overall population were significant (P < 0.01). Participants with acute fever in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014 Notes: The black line shows the proportion for each whole survey population. Differences between subsequent years in the proportion of the overall population were significant (P < 0.01). Participants aged 2 to 9 years with splenomegaly in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014 Notes: The black line shows the proportion for each whole survey population. Differences between subsequent years in the proportion of the overall population were significant (P < 0.01). Participants with anaemia in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014 Notes: The black line shows the proportion for each whole survey population. Differences between subsequent years in the proportion of the overall population were significant (P < 0.01). Anaemia was defined according to WHO recommendations, which included age-specific cut-offs and altitude corrections. Participants with severe anaemia in villages below 1600 m, national malaria surveys, Papua New Guinea, 2008–2014 Notes: The black line shows the proportion for each whole survey population. Differences between subsequent years in the proportion of the overall population were significant (P < 0.01). Severe anaemia was defined according to WHO recommendations, which included age-specific cut-offs and altitude corrections.

Discussion

Within 5 years, the prevalence of malaria in Papua New Guinea decreased from 11.1% to 0.9% and during 2013–2014 no parasites were detected by light microscopy in most provinces. This is a greater reduction than the 26% observed in Africa between 2000 and 2016. Moreover, the prevalence in 2014 was lower than that in other countries in the Asia–Pacific region, including the neighbouring Papua province of Indonesia.– An initial shift towards proportionally more P. vivax than P. falciparum infections appeared to be transient and was followed by a clear reduction in both species, as observed elsewhere., These trends are in line with previously documented declines in malaria following the introduction of long-lasting insecticide-treated nets.,, Provinces in which no malaria parasites were found should not be considered malaria-free because, as parasite density decreases, an increasing proportion of infections becomes submicroscopic,,, particularly if transmission decreases faster than the loss of immunity. In three provinces with zero prevalence, rapid diagnostic tests found that people with fever who had not left the province had a current or recent infection. Consequently, maintaining a high level of intervention coverage is crucial for avoiding resurgence. The notion that climatic change might have increased malaria in the highlands could not be substantiated. In locations above 1600 m, malaria prevalence was lower in 2010–2011 and 2013–2014 than between 2000 and 2005. The protective effect of insecticide-treated nets in both the highlands and lowlands, from where infections are often imported, may have outweighed the impact of changing weather patterns or increased people movement. Unlike in previous years,, P. falciparum was the dominant species in the highlands. The prevalence of fever and splenomegaly declined with that of parasite infection. However, the association between infection and symptoms became stronger over time, perhaps because the proportion of microscopically detectable infections that were symptomatic increased as transmission and immunity declined. The decrease in splenomegaly was most marked, which may reflect a reduction in chronic malaria infection. On the other hand, anaemia remained common, indicating that the cause is multifactorial. Anaemia may not, therefore, be useful for monitoring rapid changes in malaria prevalence. As severe anaemia, in particular, affects children’s health and development, its causes and appropriate mitigating measures should be investigated., Between 2004 and 2012, the distribution of insecticide-treated nets to households was the only large-scale malaria intervention in Papua New Guinea. The baseline survey demonstrated a strong negative association between net coverage and malaria prevalence. In the absence of other factors, such as major economic developments or a prolonged drought, it is plausible that the drop in prevalence between the 2008–2009 and 2010–2011 surveys resulted from increased provision of nets and measures promoting their use. The lack of an association between net use and malaria prevalence in the last two surveys may have been due to factors such as outdoor biting, which sustained disease transmission, and the mass effect of net use on all community members. With our survey design, it was not possible to quantify the relative contributions of net use and artemisinin-based combination therapy to the reduction in prevalence. Combination therapy was introduced in November 2011 and, by late 2012, was available at approximately half of health-care facilities. Nevertheless, although the treatment’s gametocidal effect can reduce transmission from patients, its prophylactic effect is limited. Moreover, in 2014, only 45% of patients with confirmed or suspected malaria who attended health-care facilities were treated with artemisinin-based combination therapy, which corresponds to a population coverage of 19% at best. The community benefits of combination therapy can be maximized by prompt diagnosis and treatment. With decreasing malaria prevalence, clinicians across Papua New Guinea should be encouraged to administer antimalarials only to people with a positive test result, which has proven to be a safe approach, and to thoroughly investigate the causes of nonmalarial fevers. Better guidance on differential diagnosis and on fever management is warranted. We found that individuals cohabiting with another infected person were more likely to carry parasites, possibly due to similar exposure patterns. There were fewer infections in high-quality houses occupied by better-off households, possibly because of economic factors or the building’s structure or location – most high-quality houses were in urban areas. Earlier studies in Papua New Guinea found conflicting evidence of the impact of housing, namely raised structures, on mosquito exposure., As indoor exposure to malaria vectors has been reduced by nets, people’s outdoor behaviour may be an increasingly important determinant of exposure as many vectors tend to bite outdoors., The investigation of residual malaria transmission is crucial for eliminating the disease and should take into account human and mosquito behaviour patterns, including the distribution of different Anopheles populations, their biting preferences and their susceptibility to interventions.,, In our study, we used age-standardization to account for differences in the age-composition of participants between surveys and between participants who gave blood samples and the general population. However, as the 2008–2009 survey included only districts where nets were distributed, the national prevalence of parasite infection may have been underestimated. Data from sentinel sites showed that the prevalence after net distribution was 4.8% compared with 15.7% before. In addition, the estimated prevalence in the 2010–2011 and 2013–2014 surveys may have been too low because, due to security concerns, they excluded West New Britain Province, where the prevalence is traditionally high. In conclusion, increased use of long-lasting insecticide-treated nets in Papua New Guinea was associated with a rapid and significant decline in malaria prevalence – the lowest prevalence ever recorded was in 2013–2014. The decline also occurred in the epidemic-prone highlands. Light microscopy showed that P. falciparum remained more common than P. vivax. Declining prevalence was accompanied by broader health benefits, such as decreased morbidity. However, nonmalarial fever now requires better clinical management. Research into the drivers of residual malaria transmission and the burden and role of submicroscopic parasite infection are crucial for better targeting of interventions and for eliminating the disease.
  34 in total

1.  Missing in the line of duty.

Authors:  Manuel W Hetzel; Justin Pulford; Tony Tandrapah; Sharon Jamea-Maiasa
Journal:  P N G Med J       Date:  2014 Mar-Dec

Review 2.  The epidemiology of malaria in Papua New Guinea.

Authors:  Ivo Müller; Moses Bockarie; Michael Alpers; Tom Smith
Journal:  Trends Parasitol       Date:  2003-06

3.  Increasing incidence of Plasmodium knowlesi malaria following control of P. falciparum and P. vivax Malaria in Sabah, Malaysia.

Authors:  Timothy William; Hasan A Rahman; Jenarun Jelip; Mohammad Y Ibrahim; Jayaram Menon; Matthew J Grigg; Tsin W Yeo; Nicholas M Anstey; Bridget E Barber
Journal:  PLoS Negl Trop Dis       Date:  2013-01-24

4.  The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailand-Myanmar border areas, Cambodia, and Vietnam.

Authors:  Mallika Imwong; Thuy Nhien Nguyen; Rupam Tripura; Tom J Peto; Sue J Lee; Khin Maung Lwin; Preyanan Suangkanarat; Atthanee Jeeyapant; Benchawan Vihokhern; Klanarong Wongsaen; Dao Van Hue; Le Thanh Dong; Tam-Uyen Nguyen; Yoel Lubell; Lorenz von Seidlein; Mehul Dhorda; Cholrawee Promnarate; Georges Snounou; Benoit Malleret; Laurent Rénia; Lilly Keereecharoen; Pratap Singhasivanon; Pasathorn Sirithiranont; Jem Chalk; Chea Nguon; Tran Tinh Hien; Nicholas Day; Nicholas J White; Arjen Dondorp; Francois Nosten
Journal:  Malar J       Date:  2015-09-30       Impact factor: 2.979

5.  Changes in malaria burden and transmission in sentinel sites after the roll-out of long-lasting insecticidal nets in Papua New Guinea.

Authors:  Manuel W Hetzel; Lisa J Reimer; Gibson Gideon; Gussy Koimbu; Céline Barnadas; Leo Makita; Peter M Siba; Ivo Mueller
Journal:  Parasit Vectors       Date:  2016-06-14       Impact factor: 3.876

6.  Submicroscopic and Asymptomatic Plasmodium Parasitaemia Associated with Significant Risk of Anaemia in Papua, Indonesia.

Authors:  Zuleima Pava; Faustina H Burdam; Irene Handayuni; Leily Trianty; Retno A S Utami; Yusrifar Kharisma Tirta; Enny Kenangalem; Daniel Lampah; Andreas Kusuma; Grennady Wirjanata; Steven Kho; Julie A Simpson; Sarah Auburn; Nicholas M Douglas; Rintis Noviyanti; Nicholas M Anstey; Jeanne R Poespoprodjo; Jutta Marfurt; Ric N Price
Journal:  PLoS One       Date:  2016-10-27       Impact factor: 3.240

7.  Health Worker Compliance with a 'Test And Treat' Malaria Case Management Protocol in Papua New Guinea.

Authors:  Justin Pulford; Iso Smith; Ivo Mueller; Peter M Siba; Manuel W Hetzel
Journal:  PLoS One       Date:  2016-07-08       Impact factor: 3.240

8.  The treatment of non-malarial febrile illness in Papua New Guinea: findings from cross sectional and longitudinal studies of health worker practice.

Authors:  Olga P M Saweri; Manuel W Hetzel; Ivo Mueller; Peter M Siba; Justin Pulford
Journal:  BMC Health Serv Res       Date:  2017-01-05       Impact factor: 2.655

9.  Progress in mosquito net coverage in Papua New Guinea.

Authors:  Manuel W Hetzel; Adnan A K Choudhury; Justin Pulford; Yangta Ura; Maxine Whittaker; Peter M Siba; Ivo Mueller
Journal:  Malar J       Date:  2014-06-24       Impact factor: 2.979

10.  Malaria case management in Papua New Guinea following the introduction of a revised treatment protocol.

Authors:  Justin Pulford; Serah F Kurumop; Yangta Ura; Peter M Siba; Ivo Mueller; Manuel W Hetzel
Journal:  Malar J       Date:  2013-11-27       Impact factor: 2.979

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  18 in total

1.  Status of Insecticide Resistance in Papua New Guinea: An Update from Nation-Wide Monitoring of Anopheles Mosquitoes.

Authors:  Gussy Koimbu; Cyrille Czeher; Michelle Katusele; Muker Sakur; Lemen Kilepak; Anthony Tandrapah; Manuel W Hetzel; Justin Pulford; Leanne Robinson; Stephan Karl
Journal:  Am J Trop Med Hyg       Date:  2018-01-01       Impact factor: 2.345

2.  A Randomized Open-Label Evaluation of the Antimalarial Prophylactic Efficacy of Azithromycin-Piperaquine versus Sulfadoxine-Pyrimethamine in Pregnant Papua New Guinean Women.

Authors:  Brioni R Moore; John M Benjamin; Roselyn Tobe; Maria Ome-Kaius; Gumul Yadi; Bernadine Kasian; Charles Kong; Leanne J Robinson; Moses Laman; Ivo Mueller; Stephen Rogerson; Timothy M E Davis
Journal:  Antimicrob Agents Chemother       Date:  2019-09-23       Impact factor: 5.191

3.  The relative impact of interventions on sympatric Plasmodium vivax and Plasmodium falciparum malaria: A systematic review.

Authors:  Melanie Loeffel; Amanda Ross
Journal:  PLoS Negl Trop Dis       Date:  2022-06-29

4.  Mathematical modelling of the impact of expanding levels of malaria control interventions on Plasmodium vivax.

Authors:  Michael T White; Patrick Walker; Stephan Karl; Manuel W Hetzel; Tim Freeman; Andreea Waltmann; Moses Laman; Leanne J Robinson; Azra Ghani; Ivo Mueller
Journal:  Nat Commun       Date:  2018-08-17       Impact factor: 14.919

5.  Lack of significant recovery of chloroquine sensitivity in Plasmodium falciparum parasites following discontinuance of chloroquine use in Papua New Guinea.

Authors:  Makoto Sekihara; Shin-Ichiro Tachibana; Masato Yamauchi; Shoki Yatsushiro; Steven Tiwara; Naoyuki Fukuda; Mie Ikeda; Toshiyuki Mori; Makoto Hirai; Francis Hombhanje; Toshihiro Mita
Journal:  Malar J       Date:  2018-11-26       Impact factor: 2.979

6.  Does test-based prescription of evidence-based treatment for malaria improve treatment seeking and satisfaction? Findings of repeated cross-sectional surveys in Papua New Guinea.

Authors:  Justin Pulford; Olga P M Saweri; Caroline Jeffery; Peter M Siba; Ivo Mueller; Manuel W Hetzel
Journal:  BMJ Glob Health       Date:  2018-11-16

7.  Net age, but not integrity, may be associated with decreased protection against Plasmodium falciparum infection in southern Malawi.

Authors:  Liana R Andronescu; Andrea G Buchwald; Jenna E Coalson; Lauren Cohee; Andy Bauleni; Jenny A Walldorf; Chifundo Kandangwe; Themba Mzilahowa; Terrie E Taylor; Don P Mathanga; Miriam K Laufer
Journal:  Malar J       Date:  2019-09-24       Impact factor: 2.979

8.  Spatial prediction of malaria prevalence in Papua New Guinea: a comparison of Bayesian decision network and multivariate regression modelling approaches for improved accuracy in prevalence prediction.

Authors:  Eimear Cleary; Manuel W Hetzel; Paul Siba; Colleen L Lau; Archie C A Clements
Journal:  Malar J       Date:  2021-06-13       Impact factor: 2.979

9.  The impact of the scale-up of malaria rapid diagnostic tests on the routine clinical diagnosis procedures for febrile illness: a series of repeated cross-sectional studies in Papua New Guinea.

Authors:  Justin Pulford; Serah Kurumop; Ivo Mueller; Peter M Siba; Manuel W Hetzel
Journal:  Malar J       Date:  2018-05-16       Impact factor: 2.979

10.  Malaria prevalence, knowledge, perception, preventive and treatment behavior among military in Champasak and Attapeu provinces, Lao PDR: a mixed methods study.

Authors:  Phoutnalong Vilay; Daisuke Nonaka; Phosadeth Senamonty; Malayvanh Lao; Moritoshi Iwagami; Jun Kobayashi; Paul Michael Hernandez; Ketkesone Phrasisombath; Sengchanh Kounnavong; Bouasy Hongvanthong; Paul T Brey; Shigeyuki Kano
Journal:  Trop Med Health       Date:  2019-01-25
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